https://github.com/benmarwick/ctv-archaeology
CRAN Task View: Archaeological Science
https://github.com/benmarwick/ctv-archaeology
archaeological-science archaeology cran-task data-science r task-view
Last synced: about 1 year ago
JSON representation
CRAN Task View: Archaeological Science
- Host: GitHub
- URL: https://github.com/benmarwick/ctv-archaeology
- Owner: benmarwick
- Created: 2015-01-19T10:44:41.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2025-03-15T06:12:29.000Z (about 1 year ago)
- Last Synced: 2025-04-13T04:59:28.705Z (about 1 year ago)
- Topics: archaeological-science, archaeology, cran-task, data-science, r, task-view
- Language: R
- Size: 1.98 MB
- Stars: 151
- Watchers: 36
- Forks: 44
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
CRAN Task View: Archaeological Science
--------------------------------------
[](https://zenodo.org/badge/latestdoi/29466157)
Maintainer:
Ben Marwick
Contact:
benmarwick at gmail.com
This CRAN Task View contains a list of packages useful for scientific work in Archaeology, grouped by topic. Note that this is not an official CRAN Task View, just one I have prepared for my own convenience, so it includes some packages only on GitHub and other non-CRAN resources I find useful. Many of the most highly recommended packages listed here can be installed in a single step by installing the [tidyverse](https://cran.r-project.org/package=tidyverse) package.
Besides these packages, a very wide variety of functions suitable for scientific work in Archaeology is provided by both the basic R system (and its set of recommended core packages), and a number of other packages on the Comprehensive R Archive Network (CRAN) and [GitHub](http://www.rdocumentation.org/packages?type=github). Consequently, several of the other CRAN Task Views may contain suitable packages, in particular the [Spatial](http://cran.rstudio.com/web/views/Spatial.html), [Spatio-temporal](http://cran.rstudio.com/web/views/SpatioTemporal.html), [Cluster analysis](http://cran.r-project.org/web/views/Cluster.html), [Multivariate Statistics](http://cran.r-project.org/web/views/Multivariate.html), [Bayesian inference](http://cran.r-project.org/web/views/Bayesian.html), [Visualization](http://cran.r-project.org/web/views/Graphics.html), and [Reproducible research](http://cran.r-project.org/web/views/ReproducibleResearch.html) Task Views.
Contributions to this Task View are always welcome, and encouraged. The source file for this particular task view file resides in a GitHub repository (see below), and pull requests are the preferred method for contributions.
## Table of Contents
- [CRAN Task View: Archaeological Science](#cran-task-view-archaeological-science)
- [Data acquisition](#data-acquisition)
- [Data manipulation](#data-manipulation)
- [Visualising data](#visualising-data)
- [Multi-panel plot layouts](#multi-panel-plot-layouts)
- [Analysis in general](#analysis-in-general)
- [Analysis of categorical and count data](#analysis-of-categorical-and-count-data)
- [Linear, generalized linear models, and non-linear models](#linear-generalized-linear-models-and-non-linear-models)
- [Multivariate statistics](#multivariate-statistics)
- [Making maps and using R as a Geographical Information System](#making-maps-and-using-r-as-a-geographical-information-system)
- [Environmental & geological analysis](#environmental--geological-analysis)
- [Dating](#dating)
- [Evolution, phylogenetics, morphometrics, and shape analysis](#evolution-phylogenetics-morphometrics-and-shape-analysis)
- [Image analysis](#image-analysis)
- [Simulations](#simulations)
- [Network analysis](#network-analysis)
- [Mortality Analysis](#mortality-analysis)
- [Skyscape Archaeology](#skyscape-archaeology)
- [Reproducible research](#reproducible-research)
- [Writing Reproducible manuscripts](#writing-reproducible-manuscripts)
- [Developing R code and packages](#developing-r-code-and-packages)
- [Datasets](#datasets)
- [Places to go for help](#places-to-go-for-help)
- [Related links:](#related-links)
- [Publications that include R code](#publications-that-include-r-code)
- [Contributors](#contributors)
## Data acquisition
- The ideal method is to export your spreadsheets from Excel (or whatever program you made them) as CSVs (comma-separated-values, a simple, non-proprietary plain-text-based format that is very transparent, being human-readable, easily machine-processable and suitable for archival storage) and read them into R using the base function `read.csv()`. Data in other types of plain text files can be read in with `read.table()`.
- To read Microsoft Excel files into R there is [readxl]( https://github.com/hadley/readxl). OpenDocument Spreadsheet files can be read into R using [readODS](http://cran.rstudio.com/web/packages/readODS/index.html).
- For working with untidy and/or complex Excel spreadsheets (i.e. many tables in one sheet, coloured cells, cells with formulas, etc.), use [jailbreakr](https://github.com/rsheets/jailbreakr), [xlsxtractr](https://github.com/hrbrmstr/xlsxtractr), [tidyxl](https://github.com/nacnudus/tidyxl) and [unpivotr](https://github.com/nacnudus/unpivotr)
- Text data (as in sentences and paragraphs) can be read in and analysed with the [tm](http://cran.rstudio.com/web/packages/tm/index.html) package or [tidytext](https://cran.r-project.org/package=tidytext). If the text is in a Microsoft Word file, use [textreadr](https://CRAN.R-project.org/package=textreadr), or if it's a PDF file, use [pdftools](https://CRAN.R-project.org/package=pdftools). Text in image files can be extracted with [tesseract](https://cran.r-project.org/package=tesseract)
- For quickly reading in a very large number of CSV files, or very large CSV files, use `fread()` from the [data.table](http://cran.rstudio.com/web/packages/data.table/index.html) package or functions in the [readr](https://github.com/hadley/readr) package. For plain text (CSV, TSV, etc) files that are too big to fit in memory, use [chunked](https://CRAN.R-project.org/package=chunked) to read and operate on them in small chunks.
- [RODBC](http://cran.rstudio.com/web/packages/RODBC/index.html), [RMySQL](http://cran.rstudio.com/web/packages/RMySQL/index.html), [RPostgreSQL](http://cran.rstudio.com/web/packages/RPostgreSQL/index.html), [RSQLite](http://cran.rstudio.com/web/packages/RSQLite/index.html) for connecting R to SQL databases. [RODBC](http://cran.rstudio.com/web/packages/RODBC/index.html) can connect to Microsoft Access databases.
- The [haven](https://github.com/hadley/haven) and [foreign](http://cran.rstudio.com/web/packages/foreign/index.html) packages can be used for reading and writing files from certain versions of Minitab, S, SAS, SPSS, Stata, Systat and Weka.
- ESRI shapefiles can be read using [rgdal](http://cran.rstudio.com/web/packages/rgdal/index.html) or [maptools](http://cran.rstudio.com/web/packages/maptools/index.html)
- R can receive data directly from the web using [rvest](http://cran.rstudio.com/web/packages/rvest/index.html), [httr](http://cran.rstudio.com/web/packages/httr/index.html), [XML](http://cran.rstudio.com/web/packages/XML/index.html), [jsonlite](http://cran.rstudio.com/web/packages/jsonlite/index.html), [RSelenium](http://cran.r-project.org/web/packages/RSelenium/index.html) (requires Selenium 2.0 Remote WebDriver). R can be programmed to be a web-scraper using rvest and/or Rselenium. The [Web Technologies](http://cran.r-project.org/web/views/WebTechnologies.html) task view gives more details.
- Google spreadsheets can be read into R using the [googlesheets](https://github.com/jennybc/googlesheets) package
- Tables can be read directly from Microsoft Word documents with [docxtractr](https://cran.r-project.org/web/packages/docxtractr), and from PDF documents with [tabulizer](https://github.com/leeper/tabulizer)
- Datasets from the Open Context repository can be browsed and read into R using the [opencontext](https://github.com/ropensci/opencontext) package
## Data manipulation
- [dplyr](http://cran.rstudio.com/web/packages/dplyr/index.html) and [data.table](http://cran.rstudio.com/web/packages/data.table/index.html) for splitting the data up by groups, applying some common or custom functions, and combining the output back into a convenient form (ie. typical aggregation, splitting and summarising operations). Both packages are fast on very large datasets.
- For cleaning, examining, and making quick summaries of data, [janitor](https://github.com/sfirke/janitor), [skimr](https://github.com/ropenscilabs/skimr), [statar](https://github.com/matthieugomez/statar), and [xda](https://github.com/ujjwalkarn/xda) maybe useful. [tabplot](https://github.com/mtennekes/tabplot/) has functions for exploratory data visualisation of tables
- [tidyr](http://cran.rstudio.com/web/packages/tidyr/index.html) for rearranging the data from long to wide forms, and more complex reshaping.
- [purrr](http://cran.rstudio.com/web/packages/purrr/index.html) simplifies working with lists, applying functions to list elements and collecting the results
- [broom](http://cran.rstudio.com/web/packages/broom/index.html) takes the output of many built-in functions in R, such as `lm` or `t.test`, and turns them into tidy data frames.
- [measurements](https://cran.r-project.org/web/packages/measurements/), [convertr](https://github.com/ropenscilabs/convertr), and [units](https://cran.r-project.org/web/packages/units) converts between metric and imperial units, or calculate a dimension's unknown value from other dimensions' measurements.
## Visualising data
- [ggplot2](http://cran.rstudio.com/web/packages/ggplot2/index.html) produces a very wide variety of attractive plots with a highly flexible and logical syntax.
- Extensions include [ggbiplot](https://github.com/vqv/ggbiplot) (PCA biplots with ellipses), [GGally](http://cran.r-project.org/web/packages/GGally/index.html) (plot matrices), [ggtern](http://www.ggtern.com/) (ternary plots), [ggfortify](https://github.com/sinhrks/ggfortify) (many methods for plotting PCA, clustering, linear model output, etc., using ggplot2),[ggalt](https://github.com/hrbrmstr/ggalt) (more geoms, coords, stats, scales and fonts, including splines, 1d and 2d densities), [waffle](https://github.com/hrbrmstr/waffle) (for square pie charts), [ggraph](https://github.com/thomasp85/ggraph) for treemaps, [ggfan](https://CRAN.R-project.org/package=ggfan) for fanplots, [tidybayes](https://github.com/mjskay/tidybayes) for plotting output of Bayesian analysis, [ggridges](https://CRAN.R-project.org/package=ggridges) for ridge plots, [ggalt](https://CRAN.R-project.org/package=ggalt) for many additional geoms, [ggrepel](https://github.com/slowkow/ggrepel) for moving overlapping text labels away from each other, and [shadowtext](https://cran.r-project.org/web/packages/shadowtext/) for a halo around text to make it more readable on busy plots.
- For showing distributions across several categories: [ggforce](https://CRAN.R-project.org/package=ggforce), [ggbeeswarm](https://github.com/eclarke/ggbeeswarm), [vipor](https://github.com/sherrillmix/vipor), [sinaplot](https://cran.r-project.org/web/packages/sinaplot)
- For isolines and isobands use [ggisoband](https://github.com/clauswilke/ggisoband)
- [plotly](https://github.com/ropensci/plotly) and [ggiraph](https://github.com/davidgohel/ggiraph) make ggplots interactive with mouse-over pop-ups, zooming, click-actions, etc. [scatterD3](https://github.com/juba/scatterD3) makes highly interactive scatter plots
- [circlize](https://cran.r-project.org/web/packages/circlize/index.html) implements Circos in R for circular and chord plots. Rose plots can be made with [ggplot2](http://cran.rstudio.com/web/packages/ggplot2/index.html), Schmidt diagrams can be made with the `net` function in [RFOC](https://cran.r-project.org/web/packages/RFOC) or the `Stereo*` functions in [RockFab](https://cran.r-project.org/web/packages/RockFab/)
- [plotrix](http://cran.rstudio.com/web/packages/plotrix/index.html) has the function `battleship.plot()` to make Ford's battleship diagrams.
- [ggmap](http://cran.rstudio.com/web/packages/ggmap/index.html) combines the spatial information of static maps from Google Maps, OpenStreetMap, Stamen Maps or CloudMade Maps with the layered grammar of graphics implementation of ggplot2
- Stratigraphic data plots can be drawn using [tidypaleo](https://github.com/paleolimbot/tidypaleo), the `Stratiplot()` function in [analogue](http://cran.rstudio.com/web/packages/analogue/index.html) and functions `strat.plot()` and strat.plot.simple in the [rioja](http://cran.rstudio.com/web/packages/rioja/index.html) package. The rioja package also includes `chclust()` for stratigraphically constrained clustering, and related dendrogram plotting methods.
- [rgl](http://cran.rstudio.com/web/packages/rgl/index.html) and [plotly](https://github.com/ropensci/plotly) for interactive 3D plots, and [scatterplot3d](http://cran.rstudio.com/web/packages/scatterplot3d/index.html) also draws 3D point clouds.
- [tabplot](https://github.com/mtennekes/tabplot/) for exploratory data visualisation of tables
- For schematic diagrams, such as Harris matrices, [DiagrammeR](https://github.com/rich-iannone/DiagrammeR) is useful.
- For colour schemes in plots: [viridis](https://github.com/sjmgarnier/viridis) for perfectly perceptually-uniform colours, [RColorBrewer](http://cran.r-project.org/web/packages/RColorBrewer/index.html), [wesanderson](http://cran.r-project.org/web/packages/wesanderson/index.html), and [munsell](http://cran.r-project.org/web/packages/munsell/index.html) for exploring and using the Munsell colour system, and for some extra themes for ggplot2, including some Tufte-inspired themes, see [ggthemes](http://cran.r-project.org/web/packages/ggthemes/index.html).
### Multi-panel plot layouts
- To combine and align multiple ggplot2 plots (and other image types) in one panel:
- use [cowplot](https://cran.r-project.org/web/packages/cowplot/index.html) for a publication-ready theming and labelling
- [patchwork](https://github.com/thomasp85/patchwork) for a simple grammar using `+`, `/`, etc
- [gridExtra](http://cran.rstudio.com/web/packages/gridExtra/index.html) for configuring layouts with a matrix
- [multipanelfigure](https://CRAN.R-project.org/package=multipanelfigure), perhaps the most versatile for combining different elements
## Analysis in general
- Base R, especially the stats package, has a lot of functionality useful for analysing archaeological data. For example, `chisq.test()`, `prop.test()`, `binom.test()`, `t.test()`, `wilcox.test()`, `kruskal.test()`, `mcnemar.test()`, `cor.test()`, `power.t.test()`, `power.prop.test()`, `power.anova.test()` among many others. [Hmisc](http://cran.r-project.org/web/packages/Hmisc/index.html) includes bootstrapping, setting confidence intervals, and power analysis functions, see also [psych](http://cran.r-project.org/web/packages/psych/index.html) for useful descriptive statistics and visualizations.
- [corrr](https://cran.rstudio.com/web/packages/corrr/) contains many convenient functions for exploring correlations.
- Bayesian and resampling variants of these also exist, for example in the [MCMCpack](http://cran.r-project.org/web/packages/MCMCpack/index.html), [BEST](http://cran.r-project.org/web/packages/BEST/index.html) (requires JAGS), [Bayesian First Aid](https://github.com/rasmusab/bayesian_first_aid) (also requires JAGS) packages (see the [Bayesian](http://cran.r-project.org/web/views/Bayesian.html) task view for more) and the [coin](http://cran.rstudio.com/web/packages/coin/index.html), [boot](http://cran.r-project.org/web/packages/boot/index.html), and [bootstrap](http://cran.r-project.org/web/packages/bootstrap/index.html) packages (see also [msm](http://cran.r-project.org/web/packages/msm/index.html)).
- For analysing change over time, [bcp](http://cran.r-project.org/web/packages/bcp/index.html), [changepoint](http://cran.r-project.org/web/packages/changepoint/index.html), [ecp](http://cran.r-project.org/web/packages/ecp/index.html), [AnomalyDetection](https://github.com/twitter/AnomalyDetection) and [BreakoutDetection](https://github.com/twitter/BreakoutDetection) provide functions for detecting distributional changes within time-ordered observations.
- [abc](http://cran.r-project.org/web/packages/abc/index.html) provides functions for parameter estimation, model selection, and goodness-of-fit.
## Analysis of categorical and count data
- The `table()` function in the base package and the `xtabs()` and `ftable()` functions in the stats package construct contingency tables.
- The `chisq.test()` and `fisher.test()` functions in the stats package may be used to test for independence in two-way contingency tables
- The `assocstats()` function in the vcd package computes the Pearson chi-Squared test, the Likelihood Ratio chi-Squared test, the phi coefficient, the contingency coefficient and Cramer's V for plain or stratified contingency tables.
## Linear, generalized linear models, and non-linear models
- Linear models can be fitted (via OLS) with `lm()` (from stats). The [modelr](https://github.com/hadley/modelr) package has helper functions for pipeable modelling (e.g. cross-validation, bootstrapping). For data from a non-normal population, or when there are apparent outliers, [lmPerm](https://cran.r-project.org/web/packages/lmPerm) computes linear models using permutation tests.
- Bayesian fitting of linear and non-linear models is possible with [rstanarm](https://cran.r-project.org/web/packages/rstanarm), [brms](https://github.com/paul-buerkner/brms), and [rethinking](https://github.com/rmcelreath/rethinking).
- The `nls()` function (from stats) as well as the package [minpack.lm](http://cran.rstudio.com/web/packages/minpack.lm/index.html) allow the solution of nonlinear least squares problems.
- Correlated and/or unequal variances can be modeled using the `gnls()` function of the [nlme](http://cran.rstudio.com/web/packages/nlme/index.html) package and by [nlreg](http://cran.rstudio.com/web/packages/nlreg/index.html). The nlme package is supported by Pinheiro & Bates (2000) Mixed-effects Models in S and S-PLUS, Springer, New York.
- The generic `anova()` function in the [stats](http://cran.rstudio.com/web/packages/stats/index.html) package constructs sequential analysis of variance and analysis of deviance tables, and can compute F and likelihood-ratio tests for nested models. (It is typical for other classes of statistical models in R to have anova methods as well.) The generic anova function in the [car](http://cran.rstudio.com/web/packages/car/index.html) package (associated with Fox, An R and S-PLUS Companion to Applied Regression, Sage, 2002) constructs so-called "Type-II" and "Type-III" tests for linear and generalized linear models.
- [cerUB](https://github.com/Andros-Spica/cerUB) for multivariate statistic protocols for integrating archaeometric data (geochemical, mineralogical, petrographic)
## Multivariate statistics
- The [Cluster task view](http://cran.r-project.org/web/views/Cluster.html) provides a more detailed discussion of available cluster analysis methods and appropriate R functions and packages.
- [caret](http://cran.rstudio.com/web/packages/caret/index.html) and [FactoMiner](http://cran.rstudio.com/web/packages/FactoMiner/index.html) are popular packages with a suite of multivariate methods
- [aplpack](http://cran.rstudio.com/web/packages/aplpack/index.html) provides `bagplots()`
- `lda()` and `qda()` within [MASS](http://cran.rstudio.com/web/packages/MASS/index.html) provide linear and quadratic discrimination respectively.
Model Testing and Validation
- [caret](http://cran.rstudio.com/web/packages/caret/index.html) provides many functions for model training, testing, and validation. There is also Max Kuhn's excellent companion book called "Applied Predictive Modeling" (Springer, also available as an ebook). The [mlr](http://cran.r-project.org/web/packages/mlr/index.html) package also provides classification, regression, and machine learning methods.
- Other packages that enable tuning and evaluation of models include bootstrap and [Hmisc](http://cran.rstudio.com/web/packages/Hmisc/index.html)
- The [CVtools](http://cran.rstudio.com/web/packages/CVtools/index.html) and [DAAG](http://cran.rstudio.com/web/packages/DAAD/index.html) packages include cross-validation functions for evaluating the optimality of tuning parameters such as sample sizes or number of predictors etc., in statistical models
- [rsample](https://CRAN.R-project.org/package=rsample) creates different types of resamples and corresponding classes for their analysis
Hierarchical cluster analysis
- The package [cluster](http://cran.rstudio.com/web/packages/cluster/index.html) provides functions for cluster analysis following the methods described in Kaufman and Rousseeuw (1990) Finding Groups in data: an introduction to cluster analysis, Wiley, New York
- There are also `hclust()` in the stats package and `hcluster()` in [amap](http://cran.rstudio.com/web/packages/amap/index.html)
- [pvclust](http://cran.rstudio.com/web/packages/pvclust/index.html) is a package for assessing the uncertainty in hierarchical cluster analysis. It provides approximately unbiased p-values as well as bootstrap p-values. Enhanced plotting is also available through the [dendextend](http://cran.rstudio.com/web/packages/dendextend/index.html) package.
- [dendextend](http://cran.rstudio.com/web/packages/dendextend/index.html) Offers a set of functions for extending dendrogram objects in R. It allows to both adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels - as well as visually (and statistically) compare different dendrograms to one another.
Other partitioning methods
- `kmeans()` in stats provides k-means clustering and cmeans() in [e1071](http://cran.rstudio.com/web/packages/e1071/index.html) implements a fuzzy version of the k-means algorithm. The recommended package [cluster](http://cran.rstudio.com/web/packages/cluster/index.html) also provides functions for various partitioning methodologies.
- To compute the optimum number of clusters there is the `pamk()` function in the [fpc](http://cran.rstudio.com/web/packages/fpc/index.html) package, `cascadeKM()` in [vegan](http://cran.rstudio.com/web/packages/vegan/index.html), `Mclust()` in [mclust](http://cran.rstudio.com/web/packages/mclust/index.html), `apcluster()` in [apcluster](http://cran.rstudio.com/web/packages/apcluster/index.html)
- Self-organising maps can be produced with the [kohonen](https://CRAN.R-project.org/package=kohonen)
- Percolation analysis can be produced with the [percopackage](https://github.com/SCSchmidt/percopackage)
Mixture models and model-based cluster analysis
- [mclust](http://cran.rstudio.com/web/packages/mclust/index.html) and [flexmix](http://cran.rstudio.com/web/packages/flexmix/index.html) provide implementations of model-based cluster analysis.
Principle components and other projection, scaling, and ordination methods
- Principal Components (PCA) is available via the `prcomp()` function (based on svd), `rda()` (in package [vegan](http://cran.rstudio.com/web/packages/vegan/index.html)), `pca()` (in package [labdsv](http://cran.rstudio.com/web/packages/labdsc/index.html)) and `dudi.pca()` (in package [ade4](http://cran.rstudio.com/web/packages/ade4/index.html)), provide more ecologically-orientated implementations. Plotting of PCA output is available in [ggbiplot](https://github.com/vqv/ggbiplot) and [ggfortify](https://github.com/sinhrks/ggfortify).
- Redundancy Analysis (RDA) is available via `rda()` in vegan and `pcaiv()` in ade4.
- Canonical Correspondence Analysis (CCA) is implemented in `cca()` in both vegan and ade4.
- Detrended Correspondence Analysis (DCA) is implemented in `decorana()` in vegan.
- Principal coordinates analysis (PCO) is implemented in `dudi.pco()` in ade4, `pco()` in labdsv, `pco()` in [ecodist](http://cran.rstudio.com/web/packages/ecodist/index.html), and `cmdscale()` in package [MASS](http://cran.rstudio.com/web/packages/MASS/index.html).
- Non-Metric multi-Dimensional Scaling (NMDS) is provided by `isoMDS()` in package MASS and `nmds()` in [ecodist](http://cran.rstudio.com/web/packages/ecodist/index.html). `nmds()`, a wrapper function for `isoMDS()`, is also provided by package [labdsv](http://cran.rstudio.com/web/packages/labdsv/index.html). vegan provides helper function `metaMDS()` for `isoMDS()`, implementing random starts of the algorithm and standardised scaling of the NMDS results. The approach adopted by vegan with `metaMDS()` is the recommended approach for ecological data.
- `corresp()` and `mca()` in MASS provide simple and multiple correspondence analysis respectively. [ca](http://cran.rstudio.com/web/packages/ca/index.html) also provides single, multiple and joint correspondence analysis. `ca()` and `mca()` in ade4 provide correspondence and multiple correspondence analysis respectively, as well as adding homogeneous table analysis with `hta()`. Further functionality is also available within vegan co-correspondence is available from cocorresp. [FactoMineR](http://cran.rstudio.com/web/packages/FactoMineR/index.html) provides `CA()` and `MCA()` which also enable simple and multiple correspondence analysis as well as associated graphical routines. [CAinterprTools](https://github.com/gianmarcoalberti/CAinterprTools) has functions for correspondence analysis and diagnostics.
- Seriation methods are available in [seriation](http://cran.rstudio.com/web/packages/seriation/index.html), which includes `bertinplot()` for producing battleship plots, and [CAseriation](https://github.com/gianmarcoalberti/CAseriation) which also has a battleship plotting function.
- [tabula](http://cran.rstudio.com/web/packages/tabula) provides methods to analyse and visualise archaeological count data (artifacts, faunal remains, etc.) using diversity measures and Ford (1962) and Bertin (1977) diagrams.
- [dimensio](http://cran.rstudio.com/web/packages/dimensio) provides a set of tools to compute, extract, summarize and visualize results of Principal Components Analysis (PCA) and Correspondence Analysis (CA) based on the Singular Value Decomposition (SVD). It also includes methods for partial bootstrap validation.
Dissimilarity coefficients
- `dist()` in standard package stats, `daisy()` in recommended package [cluster](http://cran.rstudio.com/web/packages/cluster/index.html), `vegdist()` in [vegan](http://cran.rstudio.com/web/packages/vegan/index.html), `dsvdis()` in [labdsv](http://cran.rstudio.com/web/packages/labdsv/index.html), `Dist()` in [amap](http://cran.rstudio.com/web/packages/amap/index.html), `distance()` in [ecodist](http://cran.rstudio.com/web/packages/ecodist/index.html), a suite of functions in [ade4](http://cran.rstudio.com/web/packages/ade4/index.html), and [rdist](http://cran.rstudio.com/web/packages/rdist/index.html) for very fast distance computations.
- [simba](http://cran.rstudio.com/web/packages/simba/index.html) provides functions for the calculation of similarity and multiple plot similarity measures with binary data (for instance presence/absence data)
- `distance()` in the [analogue](http://cran.rstudio.com/web/packages/analogue/index.html) package can be used to calculate dissimilarity between samples of one matrix and those of a second matrix. The same function can be used to produce pair-wise dissimilarity matrices, though the other functions listed above are faster. `distance()` can also be used to generate matrices based on Gower's coefficient for mixed data (mixtures of binary, ordinal/nominal and continuous variables). Function `daisy()` in package [cluster](http://cran.rstudio.com/web/packages/cluster/index.html) provides a faster implementation of Gower's coefficient for mixed-mode data than `distance()` if a standard dissimilarity matrix is required. Function `gowdis()` in package [FD](http://cran.rstudio.com/web/packages/FD/index.html) also computes Gower's coefficient and implements extensions to ordinal variables.
- [DistatisR](http://cran.rstudio.com/web/packages/DistatisR/index.html) provides functions for three-way multidimensional scaling for the analysis of multiple distance/covariance matrices collected on the same set of observations.
- Simple and partial Mantel tests to compute the Mantel statistic as a matrix correlation between two dissimilarity matrices are available in [vegan](http://cran.rstudio.com/web/packages/vegan/index.html) and [ecodist](http://cran.rstudio.com/web/packages/ecodist/index.html)
## Making maps and using R as a Geographical Information System
- Making maps: [ggspatial](http://cran.rstudio.com/web/packages/ggspatial/index.html) for easy plotting of most kinds of spatial data, see also: [maps](http://cran.rstudio.com/web/packages/maps/index.html), [rworldmap](http://cran.rstudio.com/web/packages/rworldmap/index.html), [mapdata](http://cran.rstudio.com/web/packages/mapdata/index.html), [maptools](http://cran.rstudio.com/web/packages/maptools/index.html), [mapproj](http://cran.rstudio.com/web/packages/mapproj/index.html),[mapsf](http://cran.r-project.org/web/packages/mapsf/index.html), [ggplot2](http://cran.rstudio.com/web/packages/ggplot2/index.html), [ggmap](http://cran.rstudio.com/web/packages/ggmap/index.html), [RgoogleMaps](http://cran.rstudio.com/web/packages/RgoogleMaps/index.html), [cartography](http://cran.rstudio.com/web/packages/cartography/index.html) [RColorBrewer](http://cran.rstudio.com/web/packages/RColorBrewer/index.html)
- Scale bars and North arrows can be added to maps made with ggplot and ggmap using [GISTools](https://cran.r-project.org/web/packages/GISTools), [ggsn](https://github.com/oswaldosantos/ggsn) or [legendMap](https://github.com/3wen/legendMap).
- Interactive mapping of spatial objects with zooming and panning is possible with [leaflet](https://cran.rstudio.com/web/packages/leaflet/index.html) and geo[mapview](http://cran.rstudio.com/web/packages/mapview/index.html)
- To interactively create and edit spatial objects (points, lines, polygons), use [mapedit](https://cran.r-project.org/package=mapedit), and to smooth drawn polygons, use [smoothr](https://cran.r-project.org/package=smoothr)
- R has many packages that enable it to be used as a GIS for spatial analysis: [sf](http://cran.rstudio.com/web/packages/sf/index.html), [sp](http://cran.rstudio.com/web/packages/sp/index.html), [terra](http://cran.r-project.org/web/packages/terra/index.html), [rasterVis](http://cran.rstudio.com/web/packages/rasterVis/index.html), [shapefiles](http://cran.rstudio.com/web/packages/shapefiles/index.html), [spatial](http://cran.rstudio.com/web/packages/spatial/index.html), [spatstat](http://cran.rstudio.com/web/packages/spatstat/index.html), [splancs](http://cran.rstudio.com/web/packages/splancs/index.html), [ipdw](http://cran.rstudio.com/web/packages/ipdw/index.html), [geoR](http://cran.rstudio.com/web/packages/geoR/index.html), [argosfilter](http://cran.rstudio.com/web/packages/argosfilter/index.html), [ads](http://cran.rstudio.com/web/packages/ads/index.html), [spdep](http://cran.rstudio.com/web/packages/spdep/index.html), [gstat](http://cran.rstudio.com/web/packages/gstat/index.html), [GISTools](http://cran.rstudio.com/web/packages/GISTools/index.html)
- [spgrass6](http://cran.rstudio.com/web/packages/spgrass6/index.html) and [rgrass7](http://cran.rstudio.com/web/packages/rgrass7/index.html) provides facilities for using all [GRASS](http://grass.osgeo.org/) geographical information system commands from the R command line.
- [qgisprocess](https://github.com/r-spatial/qgisprocess) establishes an interface between R and [QGIS](https://qgis.org/en/site/), i.e. it allows the user to access QGIS geoprocessing algorithms from within R (by wrapping the [qgis-process](https://docs.qgis.org/latest/en/docs/user_manual/processing/standalone.html) command line utility).
- [spdply](https://cran.r-project.org/web/packages/spdplyr) provides methods for dplyr verbs for 'sp' and 'Spatial' class objects.
- [rgdal](http://cran.rstudio.com/web/packages/rgdal/index.html) uses the GDAL (Geospatial Data Abstraction Library) (raster) and OGR (vector) data I/O library, as well as PROJ.4 for CRS (coordinate reference systems) (re)projections
- [rgeos](http://cran.rstudio.com/web/packages/rgeos/index.html) uses the GEOS (Geometry Open Source) library, which powers PostGIS: does the 'usual' geometry operations for features
- The [Spatial](http://cran.r-project.org/web/views/Spatial.html) and [Spatio Temporal](http://cran.r-project.org/web/views/SpatioTemporal.html) task views have more details.
- [recexcavAAR](https://cran.r-project.org/web/packages/recexcavAAR/index.html) 3D Reconstruction of Archaeological Excavations
- [SiteExploitationTerritories](https://github.com/eScienceCenter/SiteExploitationTerritories) implements the Tobler Hiking Function for spatial time-cost analysis of rasters
- [klrfome](https://github.com/mrecos/klrfome) provides functions to model a single scalar outcome (e.g. presence/absence of an archaeological site) to a distribution of features (such as landscape and environmental variables).
## Environmental & geological analysis
- Transfer function models including weighted averaging (WA), modern analogue technique (MAT), Locally-weighted WA, & maximum likelihood (aka Gaussian logistic) regression (GLR) are provided by [analogue](http://cran.rstudio.com/web/packages/analogue/index.html), [vegan](http://cran.rstudio.com/web/packages/vegan/index.html), and [rioja](http://cran.rstudio.com/web/packages/rioja/index.html) for stratigraphic analyses
- [G2Sd](http://cran.rstudio.com/web/packages/G2Sd/index.html) gives full descriptive statistics and a physical description of sediments based on grain-size distributions, [soiltexture](http://cran.rstudio.com/web/packages/soiltexture/index.html) and [ggtern](http://cran.rstudio.com/web/packages/ggtern/index.html) for ternary plots of soil texture
- Constrained clustering of stratigraphic data is provided by function `chclust()` in the form of constrained hierarchical clustering in [rioja](http://cran.rstudio.com/web/packages/rioja/index.html).
- Stratigraphic columns can be plotted and analysed with the the [SDAR](http://run.unl.pt/bitstream/10362/14554/1/TGEO0128.pdf) package.
- Benn diagrams can be drawn with [plotrix](http://cran.rstudio.com/web/packages/plotrix/index.html) and Woodcock diagrams with [RFOC](http://cran.rstudio.com/web/packages/RFOC/index.html).
- Function for circular statistics such as the Rayleigh test and many others, can be found in [CircStats](https://cran.r-project.org/web/packages/CircStats/index.html), [RFOC](https://cran.rstudio.com/web/packages/RFOC/index.html), [circular](https://cran.rstudio.com/web/packages/circular/index.html), [Directional](https://cran.r-project.org/web/packages/Directional/), and [heR.Misc](http://exposurescience.org/hosted-projects/inhalation-exposure-simulation-modeling-project/the-her-software-project)
- The [siar](http://cran.rstudio.com/web/packages/siar/index.html) package takes data on organism isotopes and fits a Bayesian model to their dietary habits based upon a Gaussian likelihood with a mixture dirichlet-distributed prior on the mean
- The [zooaRch](http://cran.r-project.org/web/packages/zooaRch/) package has functions for survival analysis of zooarchaeological datasets
- Functions for tree ring analysis can be found in [dplR](http://cran.rstudio.com/web/packages/dplR/index.html)
- [Orientations](https://github.com/surf3s/Orientations)for doing fabric analysis. Initially intended for use with total station coordinate data (two XYZ points on the long axis of an object) but bearing and plunge data can be transformed into the appropriate format for use here (see McPherron 2018).
- See the [Environmetrics](http://cran.r-project.org/web/views/Environmetrics.html) task view for more.
## Dating
- Radiocarbon dates can be calibrated using [Bchron](http://cran.rstudio.com/web/packages/Bchron/index.html) with various calibration curves (including user generated ones); also does Age-depth modelling, relative sea level rate estimation incorporating time uncertainty in polynomial regression models; and non-parametric phase modelling via Gaussian mixtures as a means to determine the activity of a site (and as an alternative to the Oxcal function SUM).
- [rcarbon](https://github.com/ahb108/rcarbon) for basic calibration, modelling, hypothesis testing
- Bayesian age-depth modelling of radiocarbon dates is also available in [Bacon](http://chrono.qub.ac.uk/blaauw/bacon.html), and [clam](http://chrono.qub.ac.uk/blaauw/) contains functions for "classical", non-Bayesian age-depth modelling. These are not R packages, but [clam](https://github.com/SimonGoring/clam) has been packaged for easy use.
- [c14bazAAR](https://cran.r-project.org/web/packages/c14bazAAR/index.html) for the retrieval and preparation of large radiocarbon datasets.
- The [oxcAAR](https://github.com/ISAAKiel/oxcAAR) package allows you to use R to connect to a local installation of the OxCal software to calibrate radiocarbon dates and a variety of other OxCal operations.
- [ArchaeoPhases](https://cran.r-project.org/package=ArchaeoPhases) provides statistical tools to analyze and to estimate archaeological phases from the posterior distribution (i.e. MCMC samples) of a sequence of dates. Includes testing procedures to check the presence of a gap between two successive phases or periods. [chronos](https://cran.r-project.org/package=chronos) is a fork of ArchaeoPhases v1.5 (Philippe and Vibet 2020) rewritten in S4 and using ggplot2
- Various R functions for Luminescence Dating data analysis are in the [Luminescence](http://cran.rstudio.com/web/packages/Luminescence/index.html) package (including radial plotting) and in the [numOSL](https://cran.r-project.org/web/packages/numOSL/index.html) package, including equivalent dose calculation, annual dose rate determination, growth curve fitting, decay curve decomposition, statistical age model optimization, and statistical plot visualization.
- The [archSeries](https://github.com/davidcorton/archSeries) makes chronologies from information from multiple entities with varying chronological resolution and overlapping date ranges
- The [ADMUR](https://github.com/UCL/ADMUR) package provides tools to directly model underlying population dynamics using chronological datasets (radiocarbon and other) with a variety of models, including Continuous Piecewise Linear (CPL) model framework, and model comparison framework using BIC.
- For time series analysis using calendar dates, [zoo](https://cran.r-project.org/package=zoo) and [padr](https://cran.r-project.org/package=padr) are useful.
- [SPARTAAS](https://CRAN.R-project.org/package=SPARTAAS) Statistical pattern recognition and dating using archaeological artefacts assemblages.
- [kairos](http://cran.rstudio.com/web/packages/kairos) provides methods for analysis of chronological patterns from archaeological count data, including Mean Ceramic Date (MCD)
- [nimbleCarbon](https://cran.r-project.org/package=nimbleCarbon) add on library for the [nimble](https://cran.r-project.org/package=nimble) package for Bayesian Analyses of radiocarbon dates, including phase models and custom population growth growth models.
## Tree-ring analysis / Dendrochronology
- Dendrochronology Program Library in R [dplR] (https://cran.r-project.org/web/packages/dplR/index.html) is a library that includes many tools and functions to analyze and edit tree ring series.
- [measuRing] (https://cran.r-project.org/web/packages/measuRing/index.html) provides tools to measure tree rings on scanned images of wood samples
- [RingdateR](https://ringdater.github.io/ringdater/index.html) is a graphical and statistical tool for crossdating annually resolved time series such as tree rings or mollusc, coral and otolith growth increments
## Evolution, phylogenetics, morphometrics, and shape analysis
- The [Phylogenetics task view](http://cran.r-project.org/web/views/Phylogenetics.html) provides more detailed coverage of the subject area and related functions within R.
- Packages specifically tailored for the analysis of phylogenetic and evolutionary data include: [ape](http://cran.rstudio.com/web/packages/ape/index.html), [phytools](http://cran.rstudio.com/web/packages/phytools/index.html), [phangorn](http://cran.rstudio.com/web/packages/phangorn/index.html), [Rphylip](http://cran.rstudio.com/web/packages/Rphylip/index.html) (requires PHYLIP), [ouch](http://cran.rstudio.com/web/packages/ouch/index.html), and [pegas](http://cran.rstudio.com/web/packages/pegas/index.html).
- For plotting trees most of these packages include their own modifications of the base `plot()` function, and there are also [ggtree](http://cran.rstudio.com/web/packages/ggtree/index.html), [ggdendro](http://cran.rstudio.com/web/packages/ggdendro/index.html), [dendextend](http://cran.rstudio.com/web/packages/dendextend/index.html), and [ggphylo](http://cran.rstudio.com/web/packages/ggphylo/index.html)
- Morphometric and shape analysis methods are provided by [shapes](http://cran.rstudio.com/web/packages/shapes/index.html), [geomorph](http://cran.rstudio.com/web/packages/geomorph/index.html), [paleomorph](https://cran.r-project.org/web/packages/paleomorph) and [Momocs](http://cran.rstudio.com/web/packages/Momocs/index.html). Related packages include [shapeR](https://github.com/lisalibungan/shapeR) [Anthropometry](http://cran.rstudio.com/web/packages/Anthropometry/index.html) and [Morpho](http://cran.rstudio.com/web/packages/Morpho/index.html).
- [StereoMorph](http://cran.rstudio.com/web/packages/StereoMorph/index.html) allows users to collect 3D landmarks and curves from objects using two standard digital cameras.
- [cTransmission](https://github.com/ercrema/cTransmission) provides an Approximate Bayesian Computation Framework for inferring patterns of cultural transmission from frequency data
## Image analysis
- [pixmap](http://cran.rstudio.com/web/packages/pixmap/index.html) provides methods for creating, plotting and converting bitmapped images in three different formats: RGB, grey and indexed pixmaps. Similarly, [jpeg](http://cran.rstudio.com/web/packages/jpeg/index.html) provides an easy and simple way to read, write and display bitmap images stored in the JPEG format.
- [EBImage](http://www.bioconductor.org/packages/release/bioc/html/EBImage.html) (requires ImageMagick) provides general purpose functionality for the reading, writing, processing and analysis of images (and is very well documented). Various functions for image processing and analysis can also be found in [ripa](http://cran.rstudio.com/web/packages/ripa/index.html) and [imager](https://github.com/dahtah/imager)
- [magick](https://github.com/jeroenooms/magick) provides bindings to the [ImageMagick image-processing library](http://www.imagemagick.org/), the most comprehensive open-source image processing package available.
- [iconr](https://cran.r-project.org/web/packages/iconr) analysis of Prehistoric Iconography, considers any iconographic composition (‘decoration’) as a geometric graph of graphical units (GUs)
- [outlineR](https://github.com/yesdavid/outlineR) An R package to derive outline shapes from (multiple) artefacts on JPEG images
## Simulations
- [NetLogoR](https://cran.r-project.org/package=NetLogoR) provides fucntions to easily create agent-based models in R following the NetLogo framework
- [RNetLogo](http://cran.rstudio.com/web/packages/RNetLogo/index.html) links R and NetLogo
- [simecol](http://cran.rstudio.com/web/packages/simecol/index.html) for simulating ecological (and other) dynamic systems. It can be used for differential equations, individual-based (or agent-based) and other models as well.
- One-dimensional cellular automata are also possible to model with the package [CellularAutomaton](http://cran.rstudio.com/web/packages/CellularAutomaton/index.html).
- [archeofrag](https://cran.r-project.org/package=archeofrag) for simulating site formation processes, with a particular focus on refitting and spatial analysis.
## Network analysis
- The two major packages are [igraph](http://cran.rstudio.com/web/packages/igraph/index.html), which is a generic network analysis and visualisation package, and [sna](http://cran.rstudio.com/web/packages/sna/index.html), which performs social analysis of networks.
- Other packages include [statnet](http://cran.rstudio.com/web/packages/statnet/index.html), [intergraph](http://cran.rstudio.com/web/packages/intergraph/index.html), [network](http://cran.rstudio.com/web/packages/network/index.html) (manipulates and displays network objects), [ergm](http://cran.rstudio.com/web/packages/ergm/index.html) (a set of tools to analyze and simulate networks based on exponential random graph models exponential random graph models), [hergm](http://cran.rstudio.com/web/packages/hergm/index.html) (implements hierarchical exponential random graph models), and [RSiena](http://cran.rstudio.com/web/packages/RSiena/index.html) (allows the analyses of the evolution of social networks using dynamic actor-oriented models)
## Mortality Analysis
- [mortAAR](https://cran.r-project.org/web/packages/mortAAR/index.html) Analysis of Archaeological Mortality Data
## Skyscape Archaeology
- [skyscapeR](https://github.com/f-silva-archaeo/skyscapeR) Data reduction, visualization and analysis in skyscape archaeology, archaeoastronomy and cultural astronomy
## Reproducible research
- [knitr](http://cran.rstudio.com/web/packages/knitr/index.html) enables R code and text with formatting instructions (eg. markdown or LaTeX) to be combined in a single document and executed to produce a document that contains rendered plots, analysed data and formatted text.
- The [targets](http://cran.rstudio.com/web/packages/targets) package has functions that enable declarative workflows so that each time an analysis is run, it updates only the parts of the workflow that have changed.
- [renv](http://cran.rstudio.com/web/packages/renv) supports the development of isolated, stand-alone R projects that include all the packages used and their dependencies.
- [rocker](https://github.com/rocker-org/rocker) is a project that provides Docker containers to run R in a lightweight virtual environment, the hadleyverse container includes dplyr, ggplot2, etc., as well as RStudio server and LaTeX.
### Writing Reproducible manuscripts
- [rrtools](https://github.com/benmarwick/rrtools), is a package that provides instructions, templates, and functions for making a basic compendium suitable for writing reproducible research reports and articles with R.
- The [rticles](https://github.com/rstudio/rticles) package includes templates for converting markdown documents into PDF files formatted ready for submission for publication, such as in the PLOS journals, the Frontiers In journals, and Elsevier journals. Similarly, the [papaja](https://github.com/crsh/papaja) packge contains a template for converting a markdown file into an APA-formatted PDF. These packages depend on [pandoc](http://johnmacfarlane.net/pandoc/), a universal document format converter (not an R package). In this context it is used to convert rmarkdown or LaTeX to PDF, MS Word or HTML files. It is included with RStudio but can also be used stand-alone from the command line.
- For making nice tables in documents: [kableExtra](https://cran.r-project.org/web/packages/kableExtra), [gt](https://cran.r-project.org/web/packages/gt), [flextable](https://cran.r-project.org/web/packages/flextable)
- The [quarto](http://cran.rstudio.com/web/packages/quarto) package implements markdown document formatting language for scientific and technical publishing. Quarto documents are authored using markdown with R code blocks and inline code. It has all the usual scholarly accessories: citations, figures, tables, captions and cross-referencing.
- [RStudio](http://www.rstudio.com/) is an integrated development environment that simplfies developing R code with numerous built-in conveniences, including vim
board shortcuts. There are also packages that make scholarly writing in RStudio easy: [wordcountaddin](https://github.com/benmarwick/wordcountaddin)
## Developing R code and packages
- [devtools](http://cran.rstudio.com/web/packages/devtools/index.html) (requires Rtools for Windows or Xcode for OSX) for easily creating R packages. [usethis](https://CRAN.R-project.org/package=usethis) automates many tasks surrouding package-making.
- [Goodpractice](https://github.com/MangoTheCat/goodpractice) gives advice about good practices when building R packages. Advice includes functions and syntax to avoid, package structure, code complexity, code formatting, etc.
- [roxygen2](http://cran.rstudio.com/web/packages/roxygen2/index.html) for simplifying the creation of documentation for packages,
- [testthat](http://cran.rstudio.com/web/packages/testthat/index.html) for developing tests of functions in packages
- [Style guide for writing R code](http://adv-r.had.co.nz/Style.html) by Hadley Wickham. The [lintr](http://cran.r-project.org/web/packages/lintr/) package analyses code to check that it conforms to Hadley Wickham's style guide (this package is built into RStudio)
- Idioms of R are discussed in the [vignette](http://cran.r-project.org/web/packages/rockchalk/vignettes/Rchaeology.pdf) of the [rockchalk](http://cran.rstudio.com/web/packages/rockchalk/index.html) package, and Pat Burn's essay [the R Inferno](http://www.burns-stat.com/documents/books/the-r-inferno/).
## Datasets
- [archdata](http://cran.rstudio.com/web/packages/archdata/index.html) contains eleven archaeological datasets from around the world reported in published studies. These represent typical forms of archaeological data (and so are useful for teaching)
- [binford](https://github.com/benmarwick/binford) contains more than 200 variables coding aspects of hunter-gatherer subsistence, mobility, and social organization for 339 ethnographically documented groups of hunter-gatherers, as used in Binford (2001) _Constructing Frames of Reference: An Analytical Method for Archaeological Theory Building Using Ethnographic and Environmental Data Sets_
- [bioanth](https://github.com/geanes/bioanth) contains three osteometric datasets useful for biological and forensic anthropology.
- [BSDA](http://cran.rstudio.com/web/packages/BSDA/index.html) contains a dataset of 60 radiocarbon ages of observations taken from an archaeological site with four phases of occupation.
- [cawd](https://github.com/sfsheath/cawd) contains 15 datasets of ancient Greek, Roman and Persian maps and digital atlas data
- [chemometrics](http://cran.rstudio.com/web/packages/chemometrics/index.html) contains a dataset of elemental concentrations for 180 archaeological glass vessels excavated from 15th - 17th century contexts in Antwerp.
- [folio](https://cloud.r-project.org/web/packages/folio/index.html) provides several types of data related to broad topics in archaeology (cultural evolution, radiocarbon dating, paleoenvironments, etc.), which can be used to illustrate statistical methods in the classroom (multivariate data analysis, compositional data analysis, diversity measurement, etc.).
- [neotoma](https://github.com/ropensci/neotoma) is a package that facilitates access to the Neotoma Paleoecology Dataset which contains pollen and fossil data
- [zooaRch](http://cran.r-project.org/web/packages/zooaRch/) contains two zooarchaeological datasets.
- [gsloid](https://CRAN.R-project.org/package=gsloid) Contains published data sets for global benthic d18O data for 0-5.3 Myr and global sea levels based on marine sediment core data for 0-800 ka
- [evoarchdata](https://github.com/benmarwick/evoarchdata) contains four published datasets widely used in archaeological studies of cultural evolution
## Places to go for help
- `?` function, eg. `?mean` to get built-in help on the mean function
- `sos::findFn("rose diagram")` searches all installed packages for the search term, using the [sos](http://cran.rstudio.com/web/packages/sos/index.html) package
- Most major packages come with vignettes that narrate typical uses of the package's core functions. Vignettes can be accessed with the command `vignette(packagename)`.
- Google searches in the form: [r help [search terms]](https://www.google.com/?gws_rd=ssl#q=r+help+)
- A custom search engine of R resources: http://www.rseek.org/
- [Graphical output from the examples in the documentation for all CRAN packages](http://rgm3.lab.nig.ac.jp/RGM)
- All R package documentation (including CRAN, GitHub and Bioconductor packages) is online in an easy-to-ready format at http://www.rdocumentation.org/
- Cheatsheets to print for handy reference: [short one on base](http://cran.r-project.org/doc/contrib/Short-refcard.pdf), [longer one on base](http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf), [ggplot2, dplyr, tidyr, rmarkdown, making packages](http://www.rstudio.com/resources/cheatsheets/), [data.table](https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf), [using colours](https://www.nceas.ucsb.edu/~frazier/RSpatialGuides/colorPaletteCheatsheet.pdf), [colours](http://research.stowers-institute.org/efg/R/Color/Chart/ColorChart.pdf), [numerous others](http://devcheatsheet.com/tag/r/)
- [stackoverflow](http://stackoverflow.com/questions/tagged/r) is an online Q&A point-scoring website where questions and answers can be voted on to indicate their quality. Many highly skilled R programmers are active participants. [Cross Validated](http://stats.stackexchange.com/) is a similar Q&A site for questions about statistics
- You could send a message to the official [r-help email list](https://stat.ethz.ch/mailman/listinfo/r-help), but do be sure to read, follow and cite the [posting guide](http://www.r-project.org/posting-guide.html). The list is also [searchable](https://www.google.com/?gws_rd=ssl#q=site:stat.ethz.ch+pipermail+archaeology).
## Related links:
- CRAN Task View: [SocialSciences](http://cran.rstudio.com/web/views/SocialSciences.html)
- CRAN Task View: [Spatial](http://cran.rstudio.com/web/views/Spatial.html)
- CRAN Task View: [Spatio-temporal](http://cran.r-project.org/web/views/SpatioTemporal.html)
- CRAN Task View: [Cluster analysis](http://cran.r-project.org/web/views/Cluster.html)
- CRAN Task View: [Multivariate Statistics](http://cran.nexr.com/web/views/Multivariate.html)
- CRAN Task View: [Bayesian inference](http://cran.r-project.org/web/views/Bayesian.html)
- CRAN Task View: [Phylogenetics](http://cran.r-project.org/web/views/Phylogenetics.html)
- CRAN Task View: [Robust](http://cran.r-project.org/web/views/Robust.html)
- CRAN Task View: [Visualization](http://cran.nexr.com/web/views/Graphics.html)
- CRAN Task View: [Reproducible research](http://cran.r-project.org/web/views/ReproducibleResearch.html)
- [David L. Carlson's guides on using R for 'Quantifying Archaeology' by Stephen Shennan 'Statistics for Archaeologists' by Robert Drennan]( http://people.tamu.edu/~dcarlson/quant/index.html)
- [Matt Peeples' scripts for archaeological statistics]( http://www.mattpeeples.net/resources.html)
- [Gianmarco Alberti's pages on Correspondence Analysis in Archaeology](http://cainarchaeology.weebly.com/)
- [Quantitative Archaeology Wiki](http://wiki.iosa.it/doku.php), including [some code for battleship plots](http://wiki.iosa.it/dokuwiki/doku.php?id=contingency_tables)
- [Michael Baxter's 'Notes on Quantitative Archaeology using R'](http://www.mikemetrics.com/r-chaeology/4568129078)
- [GitHub repository for this Task View](https://github.com/benmarwick/ctv-archaeology)
## Publications that include R code
Allison, James R. (2019). Ceramic Production and Exchange among the Virgin Anasazi, 30 Years Later, _KIVA_, 85:4, 289-312,
d'Alpoim Guedes J, Jin G, Bocinsky RK (2015). The Impact of Climate on the Spread of Rice to North-Eastern China: A New Look at the Data from Shandong Province. PLOS ONE 10(6): e0130430. doi:
d’Alpoim Guedes, Jade and R. Kyle Bocinsky. (2018). Climate change stimulated agricultural innovation and exchange across Asia, 2018. _Science Advances_ 4:eaar4491.
d’Alpoim Guedes, J., Hanson, S., Higham, C., Higham, T., & Lertcharnrit, T. (2019). The wet and the dry, the wild and the cultivated: Subsistence and risk management in ancient Central Thailand. Archaeological and Anthropological Sciences, 11(12), 6473–6484. https://doi.org/10.1007/s12520-019-00794-8
Angourakis, Andreas, Verònica Martínez Ferreras, Alexis Torrano, and Josep M. Gurt Esparraguera. (2018). “Presenting Multivariate Statistical Protocols in R Using Roman Wine Amphorae Productions in Catalonia, Spain.” _Journal of Archaeological Science_ 93 (May): 150–65. https://doi.org/10.1016/j.jas.2018.03.007. Describes the cerUB pkg
Arranz-Otaegui, A., Roe, J. (2023). Revisiting the concept of the ‘Neolithic Founder Crops’ in southwest Asia. Veget Hist Archaeobot (2023). https://doi.org/10.1007/s00334-023-00917-1
Arroyo-Kalin, Manuel and Riris Philip (2021). Did pre-Columbian populations of the Amazonian biome reach carrying capacity during the Late Holocene? _Philosophical Transactions of the Royal Society B: Biological Sciences_ B37620190715
Barr, W. A., Pobiner, B., Rowan, J., Du, A., & Faith, J. T. (2022). No sustained increase in zooarchaeological evidence for carnivory after the appearance of Homo erectus. _Proceedings of the National Academy of Sciences_, 119(5). https://doi.org/10.1073/pnas.2115540119
Bartholdy, B. P., & Henry, A. G. (2022). Investigating Biases Associated With Dietary Starch Incorporation and Retention With an Oral Biofilm Model. _Frontiers in Earth Science_.
Barton, C. M., Tortosa, J. E. A., Garcia-Puchol, O., Riel-Salvatore, J. G., Gauthier, N., Conesa, M. V., & Bouchard, G. P. (2017). Risk and resilience in the late glacial: A case study from the western Mediterranean. _Quaternary Science Reviews_.
Batist, Z. & Roe, J. (2024). Open archaeology, open source? Collaborative practices in an emerging community of archaeological software engineers. _Internet Archaeology_ 67.
Bebber, M. R., Kim, N. C., Tripoli, S., Quick, R., Buchanan, B., Walker, R. S., Paige, J., Baldino, J., McKinny, S., Taylor, J., & Eren, M. I. (2024). The gravity of Paleolithic hunting. _Journal of Archaeological Science: Reports_, 59, 104785. https://doi.org/10.1016/j.jasrep.2024.104785
Bebber, M.R., Buchanan, B., Eren, M.I. et al. (2023). Atlatl use equalizes female and male projectile weapon velocity. _Scientific Reports_ 13, 13349 https://doi.org/10.1038/s41598-023-40451-8
Beck, J., Gjesfjeld, E., & Chrisomalis, S. (2021). Prestige or Perish: Publishing Decisions in Academic Archaeology. _American Antiquity_, 86(4), 669-695. doi:10.1017/aaq.2021.64
Beck, J., & Smith, B. H. (2019). Don't throw the baby teeth out with the bathwater: Estimating subadult age using tooth wear in commingled archaeological assemblages. _International Journal of Osteoarchaeology_, 29(5), 831-842.
Beheim, Bret A., and Adrian V. Bell. (2011). Inheritance, Ecology and the Evolution of the Canoes of East Oceania. _Proceedings of the Royal Society B: Biological Sciences_, February.
Belmiro J., Terradas X., Cascalheira J. (2023). Creating frames of reference for chert exploitation during the Late Pleistocene in Southwesternmost Iberia. _PLOS ONE_ 18(10): e0293223. https://doi.org/10.1371/journal.pone.0293223
Belmiro, J., Bicho, N., Haws, J., & Cascalheira, J. (2020). The Gravettian-Solutrean transition in westernmost Iberia: New data from the sites of Vale Boi and Lapa do Picareiro. _Quaternary International_
Benjamin J, O’Leary M, McDonald J, Wiseman C, McCarthy J, Beckett E, et al. (2020). Aboriginal artefacts on the continental shelf reveal ancient drowned cultural landscapes in northwest Australia. PLoS ONE 15(7): e0233912.
Bergin, S., & Snitker, G. (2023). ArchaeoSRP: An R Package for Extracting and Synthesizing Federal Cultural Resources Data for Research and Management. _Advances in Archaeological Practice_, 1–11. https://doi.org/10.1017/aap.2023.22
Bevan, A., Colledge, S., Fuller, D., Fyfe, R., Shennan, S., & Stevens, C. (2017). Holocene fluctuations in human population demonstrate repeated links to food production and climate. Proceedings of the National Academy of Sciences of the United States of America, 114(49), E10524–E10531. https://doi.org/10.1073/pnas.1709190114
Bevan A. and Crema E. R. (2021). Modifiable reporting unit problems and time series of long-term human activity. _Philosophical Transactions of the Royal Society B: Biological Sciences_ B37620190726
Biagetti S, Alcaina-Mateos J, Ruiz-Giralt A, Lancelotti C, Groenewald P, Ibañez-Insa J, et al. (2021). Identifying anthropogenic features at Seoke (Botswana) using pXRF: Expanding the record of southern African Stone Walled Sites. _PLoS ONE_ 16(5): e0250776. https://doi.org/10.1371/journal.pone.0250776
Biagetti, S., Alcaina-Mateos, J., Crema, E.R., (2016). A matter of ephemerality: the study of Kel Tadrart Tuareg (southwest Libya) campsites via quantitative spatial analysis. Ecology and Society 21. https://doi.org/10.5751/ES-08202-210142 [GitHub repo](https://github.com/ercrema/a_matter_of_ephemerality).
Bicho, N. and Esteves, E. (2022). Pleistocene hunter-gatherer coastal adaptations in Atlantic Iberia. _Frontiers in Earth Sciences_ 10:957214. https://doi.org/10.3389/feart.2022.957214
Bicho, N. and Cascalheira, J. (2018). The use of lithic assemblages for the definition of short-term occupations in hunter-gatherer prehistory. In Picin, A. and Cascalheira, J. (eds.) _Short-term occupations in Paleolithic Archaeology._ Interdisciplinary Contributions to Archaeology. Springer.
Bird, Darcy et al. (2022). P3k14c, a Synthetic Global Database of Archaeological Radiocarbon Dates. _Scientific Data_ 9(1): 27.
Bird, MI, SA Condie, S O’Connor, D O’Grady, C Reepmeyer, S Ulm, M Zega, F Saltré, CJA Bradshaw. (2019). Early human settlement of Sahul was not an accident. Scientific Reports doi:10.1038/s41598-019-42946-9 https://github.com/cjabradshaw/SahulHuman
Birch, T. and M. Martinón-Torres (2019). Shape as a measure of weapon standardisation: From metric to geometric morphometric analysis of the Iron Age ‘Havor’ lance from Southern Scandinavia. _Journal of Archaeological Science_ 101: 34-51
Blinkhorn James, Timbrell Lucy, Grove Matt and Scerri Eleanor M. L. (2022). Evaluating refugia in recent human evolution in Africa _Phil. Trans. R. Soc._ B3772020048520200485
Blinkhorn, J., Groucutt, H.S., Scerri, E.M.L. et al. (2021). Directional changes in Levallois core technologies between Eastern Africa, Arabia, and the Levant during MIS 5. _Scientific Reports_ 11, 11465 https://doi.org/10.1038/s41598-021-90744-z
Borck, L., Athenstädt, J.C., Cheromiah, L.A., Aragon, L.D., Brandes, U. and Hofman, C.L., (2020). Plainware and Polychrome: Quantifying Perceptual Differences in Ceramic Classification Between Diverse Groups to Further a Strong Objectivity. Journal of Computer Applications in Archaeology, 3(1), pp.135–150. DOI:
Bourgon, N., K. Jaouen, A-M. Bacon, et al. (2021). Trophic Ecology of a Late Pleistocene Early Modern Human from Tropical Southeast Asia Inferred from Zinc Isotopes. _Journal of Human Evolution_ 161: 103075.
Bradshaw, C. J. A., Norman, K., Ulm, S., Williams, A. N., Clarkson, C., Chadœuf, J., Lin, S. C., Jacobs, Z., Roberts, R. G., Bird, M. I., Weyrich, L. S., Haberle, S. G., O’Connor, S., Llamas, B., Cohen, T. J., Friedrich, T., Veth, P., Leavesley, M., & Saltré, F. (2021). Stochastic models support rapid peopling of Late Pleistocene Sahul. Nature Communications, 12(1), 2440. https://doi.org/10.1038/s41467-021-21551-3
Bradshaw, CJA, S Ulm, AN Williams, MI Bird, RG Roberts, Z Jacobs, F Laviano, LS Weyrich, T Friedrich, K Norman, F Saltré. (2019). Minimum founding populations for the first peopling of Sahul. Nature Ecology and Evolution doi:10.1038/s41559-019-0902-6 https://github.com/cjabradshaw/SahulHuman
Breslawski RP, Etter BL, Jorgeson I, Boulanger MT (2018). The Atlatl to Bow Transition: What Can We Learn from Modern Recreational Competitions? _Lithic Technology_
Breslawski RP, Playford T (2017). Probabilistic Models of Seasonal Bison Exploitation Based on Fetal Prey Osteometry and Reproductive Phenology. _Archaeological and Anthropological Sciences_
Brown, A., & Crema, E. (2019). Maori Population Growth in Pre-contact New Zealand: regional population dynamics inferred from summed probability distributions of radiocarbon dates. _The Journal of Island and Coastal Archaeology_
Brownlee E. A Radiocarbon-Based Model of Changing Burial Rites in Early Medieval England._Radiocarbon_. 2023:1-21. https://doi.org/10.1017/RDC.2023.110
Brownlee, E. (2021). Grave Goods in Early Medieval Europe: regional variability and decline, _Internet Archaeology_ 56. https://doi.org/10.11141/ia.56.11
Broughton, J. M., & Weitzel, E. M. (2018). Population reconstructions for humans and megafauna suggest mixed causes for North American Pleistocene extinctions. Nature communications, 9(1), 5441. https://doi.org/10.1038/s41467-018-07897-1
Brunner M, von Felten J, Hinz M, Hafner A (2020). Central European Early Bronze Age chronology revisited: A Bayesian examination of large-scale radiocarbon dating. PLOS ONE 15(12): e0243719. https://doi.org/10.1371/journal.pone.0243719
Bustos-Pérez, G., & Ollé, A. (2023). The quantification of surface abrasion on flint stone tools. _Archaeometry_ https://doi.org/10.1111/arcm.12913
Bustos-Pérez, G., Baena, J., & Vaquero, M. (2023). What lies in between: Levallois, discoid and intermediate methods. _Journal of Lithic Studies_, 10(2), https://doi.org/10.2218/jls.7132
Bustos-Pérez, G., & Baena Preysler, J. (2022). Multiple approaches to predicting flake mass. _Journal of Archaeological Science: Reports_, 46, 103698. https://doi.org/10.1016/j.jasrep.2022.103698
Bustos-Pérez, G., Baena, J., (2021). Predicting Flake Mass: A View from Machine Learning. _Lithic Technology_ 14. https://doi.org/10.1080/01977261.2021.1881267
Calandra, I., Schunk, L., Bob, K., Gneisinger, W., Pedergnana, A., Paixao, E., ... & Marreiros, J. (2019). The effect of numerical aperture on quantitative use-wear studies and its implication on reproducibility. _Scientific reports_, 9(1), 1-10.
Calandra I., Schunk, L., Rodriguez, A., Gneisinger, W., Pedergnana, A., Paixao, E., Marreiros, J. (2019). Back to the edge: relative coordinate system for use-wear analysis. _Archaeological and Anthropological Sciences_.
Cardillo, M., & Charlin, J. (2018). Phylogenetic analysis of stemmed points from Patagonia: Shape change and morphospace evolution. _Journal of Lithic Studies_, 5(2). data & code: https://zenodo.org/record/4670467
Cardillo, Marcelo, Scartascini Federico Luis and Zangrando Atilio Francisco (2015). Combining morphological and metric variations in the study of design and functionality in stone weights. A comparative approach from continental and insular Patagonia, Argentina. _Journal of Archaeological Science: Reports_ 4:578-587.
Carleton, W. C. (2020). Evaluating Bayesian Radiocarbon‐dated Event Count (REC) models for the study of long‐term human and environmental processes. _Journal of Quaternary Science_ https://doi.org/10.1002/jqs.3256
Carleton W. C., Groucutt HS. (2020). Sum things are not what they seem: Problems with point-wise interpretations and quantitative analyses of proxies based on aggregated radiocarbon dates. _The Holocene_ https://doi.org/10.1177/0959683620981700
Carleton, W. C. , J. Conolly, and G. Iannone (2012). A locally-adaptive model of archaeological potential (LAMAP) _Journal of Archaeological Science_ 39(11), 3371-3385, 2012 ,
Carleton, W., McCauley, B., Costopoulos, A., & Collard, M. (2018). An evolutionary agent-based model contradicts Dunnell’s version of the waste hypothesis for cultural elaboration.
Carney, M., Tushingham, S., McLaughlin, T., & d’Alpoim Guedes, J. (2021). Harvesting strategies as evidence for 4000 years of camas (Camassia quamash) management in the North American Columbia Plateau. _Royal Society Open Science_ 8(4), 202213.
Carney, M. and Davies, B., (2020). Agent-Based Modeling, Scientific Reproducibility, and Taphonomy: A Successful Model Implementation Case Study. _Journal of Computer Applications in Archaeology_ 3(1), pp.182–196. DOI:
Carrer, F., Kossowski, T. M., Wilk, J., Pietrzak, M. B., & Bivand, R. S. (2021). The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces. _Journal of Archaeological Science_, 126, 105306.
Carrero-Pazos, M. (2023). Análisis de patrones espaciales de puntos para el estudio de tendencias locacionales en distribuciones de yacimientos arqueológicos. Vegueta: Anuario de la Facultad de Geografía e Historia, 97–114. https://doi.org/10.51349/veg.2023.1.04
Carrero-Pazos, M., Bevan, A., & Lake, M. W. (2019). The spatial structure of Galician megalithic landscapes (NW iberia): A case study from the Monte Penide region. _Journal of Archaeological Science_, 108, 104968. https://doi.org/10.1016/j.jas.2019.05.004
Carrignon, S., Brughmans, T., & Romanowska, I. (2020). Tableware trade in the Roman East: Exploring cultural and economic transmission with agent-based modelling and approximate Bayesian computation. _PloS one_, 15(11), ,[OSF repo](https://osf.io/s5mdw),[associated R code](https://github.com/simoncarrignon/abc-pandora) (notes: this paper combine multiple projects written in different C++/pyton/R)
Cascalheira, J., Gonçalves, C. and Maio D. (2020). The spatial patterning of Middle Paleolithic human settlement in westernmost Iberia. _Journal of Quaternary Science_ https://doi.org/10.1002/jqs.3286
Cascalheira, João. (2019). Territoriality and the organization of technology during the Last Glacial Maximum in southwestern Europe. _PloS one_, 14(12). https://doi.org/10.1371/journal.pone.0225828
Cegielski, W., Snitker, G., Barton, C. M., Bernabeu Aubán, J., Cortell-Nicolau, A., Pardo-Gordó, S., Bergin, S., & Castillo, A. D. (2023). A multi-method approach with machine learning to evaluating the distribution and intensity of prehistoric land use in Eastern Iberia. _Quaternary International_. https://doi.org/10.1016/j.quaint.2023.08.011
Chan, B, Francisco Gibaja J, García-Díaz V, Hoggard CS, Mazzucco N, Rowland JT, et al. (2020). Towards an understanding of retouch flakes: A use-wear blind test on knapped stone microdebitage. _PLoS ONE_ 15(12): e0243101. https://doi.org/10.1371/journal.pone.0243101
Chen, Y. and B. Marwick (2023). Women in the Lab, Men in the Field? Correlations between Gender and Research Topics at Three Major Archaeology Conferences, _Journal of Field Archaeology_, https://doi.org/10.1080/00934690.2023.2261083
Cheung, C., & Szpak, P. (2020). Interpreting Past Human Diets Using Stable Isotope Mixing Models. Journal of Archaeological Method and Theory.
Cheung, C., & Szpak, P. (2021). Interpreting Past Human Diets Using Stable Isotope Mixing Models—Best Practices for Data Acquisition. Journal of Archaeological Method and Theory.
Clarkson, C., Mike Smith, Ben Marwick, Richard Fullagar, Lynley A. Wallis, Patrick Faulkner, Tiina Manne, Elspeth Hayes, Richard G. Roberts, Zenobia Jacobs, Xavier Carah, Kelsey M. Lowe, Jacqueline Matthews, S. Anna Florin (2015). The archaeology, chronology and stratigraphy of Madjedbebe (Malakunanja II): A site in northern Australia with early occupation. _Journal of Human Evolution_ 8, 46–64 [http://dx.doi.org/10.1016/j.jhevol.2015.03.014](http://dx.doi.org/10.1016/j.jhevol.2015.03.014)
Cobos, V. A., Postillone, M. B., Bernal, V., & Perez, S. I. (2022). Spatio-temporal demographic dynamics of the human populations from Northwest Patagonia and central Chile during the Pleistocene-Holocene. _Journal of Archaeological Science: Reports_, 44, 103547. https://doi.org/10.1016/j.jasrep.2022.103547
Cochrane, E. E., Tautunu, A. A. M. M., & DiNapoli, R. J. (2019). Hypotheses to explain the few early coastal archaeological deposits in Sāmoa: Preliminary evaluations. _Journal of Archaeological Science: Reports_, 26, 101931.
Coco, E., & Iovita, R. (2020). Time-dependent taphonomic site loss leads to spatial averaging: implications for archaeological cultures. _Humanities and Social Sciences Communications_, 7(1), 1-9.
Coco, E., Holdaway, S. & Iovita, R. (2020). The Effects of Secondary Recycling on the Technological Character of Lithic Assemblages. _Journal of Paleolithic Archaeology_
Codding, B. F., Brenner Coltrain, J., Louderback, L., Vernon, K. B., Magargal, K. E., Yaworsky, P. M., Robinson, E., Brewer, S. C., & Spangler, J. D. (2022). Socioecological Dynamics Structuring the Spread of Farming in the North American Basin-Plateau Region. Environmental Archaeology, 27(4), 434–446. https://doi.org/10.1080/14614103.2021.1927480
Cole, K. E., Yaworsky, P. M., & Hart, I. A. (2022). Evaluating statistical models for establishing morphometric taxonomic identifications and a new approach using Random Forest. _Journal of Archaeological Science_ 143, 105610. https://doi.org/10.1016/j.jas.2022.105610
Coltofean-Arizancu, L., Gaydarska, B., Plutniak, S., Mary, L., Hlad, M., Algrain, I., Sengeløv, A. (2023). Harassment, assault, bullying and intimidation (HABI) in archaeology: A Europe-wide survey. _Antiquity_ 1-19. http://doi.org/10.15184/aqy.2023.58
Conrad, C., R. Shoocongdej, B. Marwick, et al. (2021). Re-Evaluating Pleistocene–Holocene Occupation of Cave Sites in North-West Thailand: New Radiocarbon and Luminescence Dating. _Antiquity_ https://doi.org/10.15184/aqy.2021.44
Conrad, C., Higham, C., Eda, M. and Marwick, B. (2016). Paleoecology and Forager Subsistence Strategies During the Pleistocene-Holocene Transition: A Reinvestigation of the Zooarchaeological Assemblage from Spirit Cave, Mae Hong Son Province, Thailand. _Asian Perspectives_ 55(1). https://github.com/cylerc/AP_SC
Contreras, Daniel A., Joël Guiot, Romain Suarez, and Alan Kirman. (2018). "Reaching The Human Scale: A Spatial and Temporal Downscaling Approach To The Archaeological Implications Of Paleoclimate Data." _Journal of Archaeological Science_ 93:54-67.[doi:10.1016/j.jas.2018.02.013](https://doi.org/10.1016/j.jas.2018.02.013)
Contreras, Daniel A. and John Meadows. (2014). “Summed radiocarbon calibrations as a population proxy: a critical evaluation using a realistic simulation approach.” _Journal of Archaeological Science_ 52:591-608. [doi:10.1016/j.jas.2014.05.030](http://www.sciencedirect.com/science/article/pii/S0305440314002088)
Coto-Sarmiento, M. & Rubio-Campillo, X. (2021). The tracing of trade: Exploring the patterns of olive oil production and distribution from Roman Baetica. Archaelogical and Anthropological Sciences,13,70.
Coto-Sarmiento, M., Rubio-Campillo, X., Remesal, J., (2018). Identifying social learning between Roman amphorae workshops through morphometric similarity. _Journal of Archaeological Science_ 96, 117–123. ,
Courtenay, L.A., Herranz-Rodrigo, D., González-Aguilera, D. et al. (2021). Developments in data science solutions for carnivore tooth pit classification. _Scientific Reports_ 11, 10209
Cortell-Nicolau, A., García-Puchol, O., & Juan-Cabanilles, J. (2023). The geometric microliths of cueva de la cocina and their significance in the mesolithic of Eastern Iberia: A morphometric study. _Quaternary International_ https://doi.org/10.1016/j.quaint.2023.05.014
Cortell-Nicolau A, García-Puchol O, Barrera-Cruz M, García-Rivero D (2021). The spread of agriculture in Iberia through Approximate Bayesian Computation and Neolithic projectile tools. PLoS ONE 16(12): e0261813. doi:10.1371/journal.pone.0261813
Crawford, K., Huster, A., Peeples, M., Gauthier, N., Smith, M., Lobo, J., Lawrence, D. (2023). A systematic approach for studying the persistence of settlements in the past. Antiquity, 97(391), 213-230. https://doi.org/10.15184/aqy.2022.175
Crema, E. R., Stevens, C. J., & Shoda, S. (2022). Bayesian analyses of direct radiocarbon dates reveal geographic variations in the rate of rice farming dispersal in prehistoric Japan. _Science Advances_, 8(38), eadc9171. https://doi.org/10.1126/sciadv.adc9171
Crema, E. R. (2022). Statistical Inference of Prehistoric Demography from Frequency Distributions of Radiocarbon Dates: A Review and a Guide for the Perplexed. _Journal of Archaeological Method Theory_ https://doi.org/10.1007/s10816-022-09559-5
Crema ER, Shoda S (2021). A Bayesian approach for fitting and comparing demographic growth models of radiocarbon dates: A case study on the Jomon-Yayoi transition in Kyushu (Japan). _PLOS ONE_ 16(5): e0251695. https://doi.org/10.1371/journal.pone.0251695
Crema, E. R., and A. Bevan (2020). INFERENCE FROM LARGE SETS OF RADIOCARBON DATES: SOFTWARE AND METHODS. _Radiocarbon_ :1–17. https://doi.org/10.1017/RDC.2020.95
Crema, E.R., Kandler, A., Shennan, S., (2016). Revealing patterns of cultural transmission from frequency data: equilibrium and non-equilibrium assumptions, _Scientific Reports_ 6, 39122.
Crema, E. R., J. Habu, K. Kobayashi and M. Madella (2016). "Summed Probability Distribution of 14C Dates Suggests Regional Divergences in the Population Dynamics of the Jomon Period in Eastern Japan." [_PLoS ONE_ 11(4): e0154809.](http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0154809), [GitHub repo](https://github.com/ercrema/Jomon_SPD_Comparison), [Zenodo repo](http://dx.doi.org/10.5281/zenodo.47339).
Crema, E.R., K. Edinborough, Giusti, D., Konidaris, G. E., Tourloukis, V., Marini, M., Maron, M., Zerboni, A., … Harvati, K. (2019). Recursive anisotropy: a spatial taphonomic study of the Early Pleistocene vertebrate assemblage of Tsiotra Vryssi, Mygdonia Basin, Greece. Boreas, 0(0). https://doi.org/10.1111/bor.12368T.
Crema, E.R., Kerig, S.J. Shennan (2014). An Approximate Bayesian Computation approach for inferring patterns of cultural evolutionary change, _Journal of Archaeological Science_, Volume 50 Pages 160-170 http://dx.doi.org/10.1016/j.jas.2014.07.014
Crema, E.R., Bevan, A., Shennan, S. (2017). Spatio-temporal approaches to archaeological radiocarbon dates. Journal of Archaeological Science 87, 1-9.https://github.com/ercrema/JAS2017_spatialSPD
Crema E.R. (2014). A simulation model of fission-fusion dynamics and long-term settlement change. Journal of Archaeological Method and Theory , 21, 385-404 https://github.com/ercrema/fissionfusion2014
Crema, E.R., Lake, M. (2015) Cultural Incubators and Spread of Innovation (2015), Human Biology, 87 (3), 151-168 https://github.com/ercrema/CulturalIncubatorSourceCodes
Crema, E.R., Kobayashi, K., (2020). A multi-proxy inference of Jōmon population dynamics using bayesian phase models, residential data, and summed probability distribution of 14C dates. Journal of Archaeological Science 117, 105136. https://doi.org/10.1016/j.jas.2020.105136 [GitHub repo](https://github.com/ercrema/jomonPhasesAndPopulation), [Zenodo repo](https://doi.org/10.5281/zenodo.3719507).
Crema, E. R. (2024). A Bayesian alternative for aoristic analyses in archaeology. _Archaeometry_. https://doi.org/10.1111/arcm.12984
Crema, E. R., Bloxam, A., Stevens, C. J., & Vander Linden, M. (2024). Modelling diffusion of innovation curves using radiocarbon data. _Journal of Archaeological Science_, 165, 105962.
Cucart-Mora, C., Gómez-Puche, M., Romano, V. et al. (2022). Reconstructing Mesolithic social networks on the Iberian Peninsula using ornaments. _Archaeological and Anthropological Sciences_ 14, 174. https://doi.org/10.1007/s12520-022-01641-z
Daems, D., Coco, E., Gillreath-Brown, A., & Kafetzaki, D. (2023). The Effects of Time-Averaging on Archaeological Networks. _Journal of Archaeological Method and Theory_ https://doi.org/10.1007/s10816-023-09608-7
Danielisová, A., Pajdla, P., Bursák, D., Strnad, L., Trubač, J. and Kmošek, J., (2021). Claiming the land or protecting the goods? The Duchcov hoard in Bohemia as a proxy for ‘Celtic migrations’ in Europe in the 4th century BCE. Journal of Archaeological Science 127, 105314. [https://doi.org/10.1016/j.jas.2020.105314](https://doi.org/10.1016/j.jas.2020.105314); [GitHub repo](https://github.com/petrpajdla/duchcov_si).
Dapschauskas, R., Göden, M. B., Sommer, C., & Kandel, A. W. (2022). The Emergence of Habitual Ochre Use in Africa and its Significance for The Development of Ritual Behavior During The Middle Stone Age. _Journal of World Prehistory_, 35(3), 233–319. https://doi.org/10.1007/s10963-022-09170-2. [Zenodo repo](https://doi.org/10.5281/zenodo.5883926)
Davis, D.S., G. Caspari, C. P. Lipo, and M. C. Sanger (2021). Deep Learning Reveals Extent of Archaic Native American Shell-Ring Building Practices. _Journal of Archaeological Science_ 132: 105433. https://doi.org/10.1016/j.jas.2021.105433
Davis, D. S., Andriankaja, V., Carnat, T. L., Chrisostome, Z. M., Colombe, C., Fenomanana, F., Hubertine, L., Justome, R., Lahiniriko, F., Léonce, H., Manahira, G., Pierre, B. V., Roi, R., Soafiavy, P., Victorian, F., Voahirana, V., Manjakahery, B., & Douglass, K. (2020). Satellite-based remote sensing rapidly reveals extensive record of Holocene coastal settlement on Madagascar. Journal of Archaeological Science, 115, 105097. https://doi.org/10.1016/j.jas.2020.105097
Davis, D. S., DiNapoli, R. J., Sanger, M. C., & Lipo, C. P. (2020). The Integration of Lidar and Legacy Datasets Provides Improved Explanations for the Spatial Patterning of Shell Rings in the American Southeast. Advances in Archaeological Practice, 8(4), 361–375. https://doi.org/10.1017/aap.2020.18
Davis, D.S.; DiNapoli, R.J.; Douglass, K. (2020). Integrating Point Process Models, Evolutionary Ecology and Traditional Knowledge Improves Landscape Archaeology—A Case from Southwest Madagascar. _Geosciences_ , 10, 287.
de la Peña P, Thomas M, Molefyane TR (2022). Particle size distribution: An experimental study using southern African reduction methods and raw materials. _PLOS ONE_ 17(12): e0278867. https://doi.org/10.1371/journal.pone.0278867
Díaz-Rodríguez, M. Ramón Fábregas-Valcarce, Augusto Pérez-Alberti (2023). A predictive model for Palaeolithic sites: A case study of Monforte de Lemos basin, NW Iberian Peninsula, _Journal of Archaeological Science: Reports_, Volume 49, 104012, https://doi.org/10.1016/j.jasrep.2023.104012
Díaz-Rodríguez, M., & Fábregas-Valcarce, R. (2022). Evaluating the effectiveness of three spatial cluster analysis methods on Palaeolithic site location distributions in Galicia, NW Iberian Peninsula. _Journal of Archaeological Science: Reports_, 41, 103323. https://doi.org/10.1016/j.jasrep.2021.103323
DiNapoli, R. J., Crema, E. R., Lipo, C. P., Rieth, T. M., & Hunt, T. L. (2021). Approximate Bayesian Computation of radiocarbon and paleoenvironmental record shows population resilience on Rapa Nui (Easter Island). Nature Communications, 12(1), 3939. https://doi.org/10.1038/s41467-021-24252-z
DiNapoli, R. J., Rieth, T. M., Lipo, C. P., & Hunt, T. L. (2020). A model-based approach to the tempo of “collapse”: The case of Rapa Nui (Easter Island). _Journal of Archaeological Science_, 105094.
DiNapoli, R. J., Lipo, C. P., Brosnan, T., Hunt, T. L., Hixon, S., Morrison, A. E., & Becker, M. (2019). Rapa Nui (Easter Island) monument (ahu) locations explained by freshwater sources. PLOS ONE, 14(1), e0210409. https://doi.org/10.1371/journal.pone.0210409
Dolbunova, E., Lucquin, A., McLaughlin, T.R. et al. (2022) The transmission of pottery technology among prehistoric European hunter-gatherers. Nature Human Behavior https://doi.org/10.1038/s41562-022-01491-8
Dombrosky, J., Ainsworth, C. S., Judkins, A. A., Valesca Meyer, J., Adler, M. A., & Lena Jones, E. (2023). Reconsidering archaeological garden hunting: A view from the northern U.S. Southwest. _Journal of Archaeological Science: Reports_, 51, 104194. https://doi.org/10.1016/j.jasrep.2023.104194
Dombrosky, Jonathan, Thomas F. Turner, Alexandra Harris, and Emily Lena Jones. (2022). “Body Size from Unconventional Specimens: A 3D Geometric Morphometrics Approach to Fishes from Ancestral Pueblo Contexts.” _Journal of Archaeological Science_ 142: 105600.
Dombrosky, J. (2020). A ~1000-year 13C Suess correction model for the study of past ecosystems. _The Holocene_, 30(3), 474–478. https://doi.org/10.1177/0959683619887416
Dosseto, A,. and B. Marwick (2022). UThwigl — An R Package for Closed- and Open-System Uranium–Thorium Dating. _Quaternary Geochronology_ 67: 101235 https://doi.org/10.1016/j.quageo.2021.101235
Drake BL, Wills WH, Hamilton MI, Dorshow W (2014). Strontium Isotopes and the Reconstruction of the Chaco Regional System: Evaluating Uncertainty with Bayesian Mixing Models. PLoS ONE 9(5): e95580. [doi:10.1371/journal.pone.0095580](http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0095580)
Drake, Brandon L., David T. Hanson, James L. Boone (2012). The use of radiocarbon-derived Δ13C as a paleoclimate indicator: applications in the Lower Alentejo of Portugal, _Journal of Archaeological Science_, Volume 39, Issue 9, September 2012, Pages 2888-2896, [http://dx.doi.org/10.1016/j.jas.2012.04.027](http://www.sciencedirect.com/science/article/pii/S0305440312001471)
Drake, Brandon L., (2012). The influence of climatic change on the Late Bronze Age Collapse and the Greek Dark Ages, _Journal of Archaeological Science_, Volume 39, Issue 6, June 2012, Pages 1862-1870 [http://dx.doi.org/10.1016/j.jas.2012.01.029](http://www.sciencedirect.com/science/article/pii/S0305440312000416)
Drake, Brandon L., WH Wills, and Erik B Erhardt (2012). The 5.1 ka aridization event, expansion of piñon-juniper woodlands, and the introduction of maize (Zea mays) in the American Southwest The Holocene December 2012 22: 1353-1360, first published on July 9, 2012 [doi:10.1177/0959683612449758](http://hol.sagepub.com/content/22/12/1353.short)
Dye, T. S., Buck, C. E., DiNapoli, R. J., & Philippe, A. (2023). Bayesian chronology construction and substance time. Journal of Archaeological Science, 153, 105765. https://doi.org/10.1016/j.jas.2023.105765
Dye, Thomas S. (2011). “A Model-based Age Estimate for Polynesian Colonization of Hawai‘i”. _Archaeology in Oceania_ 46, pp. 130–138 [https://github.com/tsdye/hawaii-colonization](https://github.com/tsdye/hawaii-colonization)
Dye, T. S. (2016). "Long-term rhythms in the development of Hawaiian social stratification." _Journal of Archaeological Science_ 71: 1-9.
Eberl, M., Bell, C., Spencer-Smith, J., Raj, M., Sarubbi, A., Johnson, P., McBride, M. (2023). Machine Learning–Based Identification of Lithic Microdebitage. Advances in Archaeological Practice, 1-12. http://doi.org/10.1017/aap.2022.35
Edinborough, K., Porčić, M., Martindale, A., Brown, T. J., Supernant, K., & Ames, K. M. (2017). Radiocarbon test for demographic events in written and oral history. _Proceedings of the National Academy of Sciences_, 114(47), 12436-12441.
Ellis, E.C., N. Gauthier, K. Klein Goldewijk, R. Bliege Bird, N. Boivin, S. Diaz, D. Fuller, J. Gill, J. Kaplan, N. Kingston, H. Locke, C. McMichael, D. Ranco, T. Rick, M.R. Shaw, L. Stephens, J.C. Svenning, J.E.M. Watson, (2021). People have shaped most of terrestrial nature for at least 12,000 years. _Proceedings of the National Academy of Sciences_. https://doi.org/10.1073/pnas.2023483118
Falcucci, A., Giusti, D., Zangrossi, F. et al. (2025). Refitting the Context: A Reconsideration of Cultural Change among Early Homo sapiens at Fumane Cave through Blade Break Connections, Spatial Taphonomy, and Lithic Technology. _Journal of Paleolithic Archaeology_ 8, 2 https://doi.org/10.1007/s41982-024-00203-0
Falcucci, A., Arrighi, S., Spagnolo, V. et al. (2024). A pre-Campanian Ignimbrite techno-cultural shift in the Aurignacian sequence of Grotta di Castelcivita, southern Italy. _Scientific Reports_ 14, 12783 https://doi.org/10.1038/s41598-024-59896-6
Falcucci, A., Karakostis, F. A., Göldner, D., & Peresani, M. (2022). Bringing shape into focus: Assessing differences between blades and bladelets and their technological significance in 3D form. _Journal of Archaeological Science: Reports_, 43, 103490. https://doi.org/10.1016/j.jasrep.2022.103490
Falcucci, A., & Peresani, M. (2022). The contribution of integrated 3D model analysis to Protoaurignacian stone tool design. _PLOS ONE_, 17(5), e0268539. https://doi.org/10.1371/journal.pone.0268539
Falótico, T., Valença, T., Verderane, M. P., & Fogaça, M. D. (2022). Stone tools differences across three capuchin monkey populations: Food’s physical properties, ecology, and culture. _Scientific Reports_, 12(1), Article 1. https://doi.org/10.1038/s41598-022-18661-3
Farahani, A., Miller, M. J., Porter, B. W., Dawson, T., & Routledge, B. (2023). Stable isotopes of archaeological and modern semi-terrestrial crabs (Potamon potamios) provide paleoecological insights into brachyuran ecology and human resource acquisition in late Holocene Jordan. _Quaternary International_. https://doi.org/10.1016/j.quaint.2023.03.001
Farahani, A. (2018). A 2500-year historical ecology of agricultural production under empire in Dhiban, Jordan. _Journal of Anthropological Archaeology_, 52, 137-155.
Field, S., Glowacki, D.M. & Gettler, L.T. (2022). The Importance of Energetics in Archaeological Least Cost Analysis. _Journal of Archaeological Method and Theory_ https://doi.org/10.1007/s10816-022-09564-8
Fitzhugh, B., Brown, W. A., Misarti, N., Takase, K., & Tremayne, A. H. (2022). Human Paleodemography and Paleoecology of the North Pacific Rim from the Mid to Late Holocene. _Quaternary Research_ 108, 123–149. https://doi.org/10.1017/qua.2022.35
Florin, S.A., Roberts, P., Marwick, B. et al. (2021). Pandanus nutshell generates a palaeoprecipitation record for human occupation at Madjedbebe, northern Australia. _Nature Ecology and Evolution_
Foecke, K. K., Hammond, A. S., & Kelley, J. (2022). Portable x-ray fluorescence spectroscopy geochemical sourcing of Miocene primate fossils from Kenya. _Journal of Human Evolution_, 170, 103234. https://doi.org/10.1016/j.jhevol.2022.103234
Fontana, G., & Bernard, S. (2023). A new method for the energetics analysis of polygonal masonry in Samnite hillforts (Italy). _Journal of Archaeological Science_, 105730. https://doi.org/10.1016/j.jas.2023.105730
Freeman, J., Robinson, E., Beckman, N. G., Bird, D., Baggio, J. A., & Anderies, J. M. (2020). The global ecology of human population density and interpreting changes in paleo-population density. _Journal of Archaeological Science_, 120, 105168.
Frederiks, P. L. (2022). Rekonstruktion einer übermoorten, prähistorischen Landschaft bei Wanna, Ldkr. Cuxhaven. Siedlungs- und Küstenforschung im südlichen Nordseegebiet 45, 43–100. https://zenodo.org/record/7404607
Fusco, M., Carletti, E., Gallinaro, M., Zerboni, A., & Spinapolice, E. (2021). Lithic variability and raw material exploitation at the Middle Stone Age (MSA) site of Gotera, southern Ethiopia: A combined technological and quantitative approach. _Journal of Lithic Studies_, 8(1), 29 p. https://doi.org/10.2218/jls.6530
Gantley, M., Whitehouse, H., & Bogaard, A. (2018). Material Correlates Analysis (MCA): An Innovative way of Examining Questions in Archaeology Using Ethnographic Data. _Advances in Archaeological Practice_, 6(4), 328-341. http://doi.org/10.1017/aap.2018.9
Garland, N. (2021). TRAC at 30: A Bibliometric Analysis of the TRAC Community. _Theoretical Roman Archaeology Journal_, 4(1), Article 1. https://doi.org/10.16995/traj.4344
Garvey, Raven. (2018). Current and potential roles of archaeology in the development of cultural evolutionary theory. Philosophical Transactions of the Royal Society B: Biological Sciences, 373(1743), 20170057. https://doi.org/10.1098/rstb.2017.0057
Gaydarska, B., Roe, J., & Slavchev, V., (2024). Dietary Variability in the Varna Chalcolithic Cemeteries. _European Journal of Archaeology_.
Gauthier, Nicolas (2021). Hydroclimate variability influenced social interaction in the prehistoric american southwest. _Frontiers in Earth Science_ 8:713. DOI:10.3389/feart.2020.620856.
Giomi, E., Mills, B. J., Aragon, L. D., Bellorado, B. A., & Peeples, M. A. (2021). Reading between the Lines: The Social Value of Dogoszhi Style in the Chaco World. _American Antiquity_, 1–24. https://doi.org/10.1017/aaq.2021.50
Giusti, D., Konidaris, G. E., Tourloukis, V., Marini, M., Maron, M., Zerboni, A., … Harvati, K. (2019). Recursive anisotropy: a spatial taphonomic study of the Early Pleistocene vertebrate assemblage of Tsiotra Vryssi, Mygdonia Basin, Greece. _Boreas_, 48(3), 713--730. https://doi.org/10.1111/bor.12368
Giusti, D., Tourloukis, V., Konidaris, G., Thompson, N., Karkanas, P., Panagopoulou, E., & Harvati, K. (2018). Beyond maps: patterns of formation processes at the Middle Pleistocene open-air site of Marathousa 1, Megalopolis Basin, Greece. _Quaternary International_ 497, 137--153
Giusti, D. and M. Arzarello, (2016). The need for a taphonomic perspective in spatial analysis: Formation processes at the Early Pleistocene site of Pirro Nord (P13), Apricena, Italy, _Journal of Archaeological Science: Reports_ 8, 235--249 code and data:
Goder-Goldberger, M., Marreiros, J., Paixão, E. et al. (2025). Incised stone artefacts from the Levantine Middle Palaeolithic and human behavioural complexity. _Archaeological and Anthropological Sciences_ 17, 27 https://doi.org/10.1007/s12520-024-02111-4
González-Molina I, Jiménez-García B, Maíllo-Fernández JM, Baquedano E, Domínguez-Rodrigo M (2020). Distinguishing Discoid and Centripetal Levallois methods through machine learning. _PLOS ONE_ 15(12): e0244288.
Graham, S., Gupta, N., Smith, J., Angourakis, A., Reinhard, A., Ellenberger, K., Batist, Z., Rivard, J., Marwick, B., Carter, M., Compton, B., Blades, R., Wood, C., Nobles, G. (2019). _The Open Digital Archaeology Textbook_ Code notebooks and repositories, and text source at
Gravel-Miguel, C., De Vynck, J., Wren, C. D., Murray, J. K., & Marean, C. W. (2022). Were prehistoric coastal sites more intensively occupied than inland sites? Using an agent-based model to understand the intensity of prehistoric coastal occupation, and what it means for studies on the evolution of the coastal adaptation. _Quaternary International_ https://doi.org/10.1016/j.quaint.2022.02.003
Gravel-Miguel, C., Murray, J. K., Schoville, B. J., Wren, C. D., & Marean, C. W. (2021). Exploring variability in lithic armature discard in the archaeological record. _Journal of Human Evolution_, 155, 102981.
Gregory, A., Mitchell, P. & Pargeter, J. (2023). Raw Material Surveys and Their Behavioral Implications in Highland Lesotho. _Journal of Paleolithic Archaeology_ 6, 18 https://doi.org/10.1007/s41982-023-00138-y
Großmann R, Weinelt M, Müller J (2023). Demographic dynamics between 5500 and 3500 calBP (3550–1550 BCE) in selected study regions of Central Europe and the role of regional climate influences. PLOS ONE 18(10): e0291956. https://doi.org/10.1371/journal.pone.0291956
Groucutt, H. S., Carleton, W. C., Fenech, K., Gauci, R., Grima, R., Scerri, E. M. L., Stewart, M., & Vella, N. C. (2022). The 4.2 ka Event and the End of the Maltese “Temple Period.” Frontiers in Earth Science, 9, 1227.
Groucutt, H.S., White, T.S., Scerri, E.M.L. et al. (2021). Multiple hominin dispersals into Southwest Asia over the past 400,000 years. _Nature_
Hageneuer, S. & Schmidt, S. C. (2019). Monumentality by numbers. In: Buccellati, F., Hageneuer, S., van der Heyden, S. & Levenson, F. (Eds.), _Size Matters - Understanding Monumentality Across Ancient Civilizations_. Bielefeld: transcript Verlag: 291-308. https://doi.org/10.14361/9783839445389-017
Hatton, A., Breeze, P. S., Guagnin, M., al-Jibrin, F., Alsharekh, A. M., Petraglia, M., & Groucutt, H. S. (2024). Landscape positioning of Neolithic mustatil stone structures along the margins of the Nefud Desert, Saudi Arabia. _The Holocene_ https://doi.org/10.1177/09596836241275010
Hatton A., Collins B, Schoville BJ, Wilkins J (2022). Ostrich eggshell beads from Ga-Mohana Hill North Rockshelter, southern Kalahari, and the implications for understanding social networks during Marine Isotope Stage 2. PLoS ONE 17(6): e0268943. http://doi.org/10.1371/journal.pone.0268943
Hausmann, N., Meredith-Williams, M., & Laurie, E. (2020). Shellfish resilience to prehistoric human consumption in the southern Red Sea: Variability in Conomurex fasciatus across time and space. _Quaternary International_. http://doi.org/10.1016/j.quaint.2020.04.034
Hecht, E.E., Pargeter, J., Khreisheh, N. et al. (2023). Neuroplasticity enables bio-cultural feedback in Paleolithic stone-t