https://github.com/markvanderloo/simputation

Making imputation easy
https://github.com/markvanderloo/simputation

data-science imputation officialstatistics r rstats

Last synced: about 2 months ago
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Making imputation easy

• Host: GitHub
• URL: https://github.com/markvanderloo/simputation
• Owner: markvanderloo
• License: gpl-3.0
• Created: 2016-07-20T14:58:27.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2024-06-14T09:20:24.000Z (3 months ago)
• Last Synced: 2024-07-28T09:34:33.914Z (about 2 months ago)
• Topics: data-science, imputation, officialstatistics, r, rstats
• Language: R
• Homepage:
• Size: 735 KB
• Stars: 89
• Watchers: 4
• Forks: 11
• Open Issues: 15
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        


[![CRAN](http://www.r-pkg.org/badges/version/simputation)](https://CRAN.R-project.org/package=simputation)[![status](https://tinyverse.netlify.app/badge/simputation)](https://CRAN.R-project.org/package=simputation)

[![Downloads](http://cranlogs.r-pkg.org/badges/simputation)](https://CRAN.R-project.org/package=simputation)[![Mentioned in Awesome Official Statistics ](https://awesome.re/mentioned-badge.svg)](http://www.awesomeofficialstatistics.org)

# simputation

An R package to make imputation simple. Currently supported methods include

- Model based (optionally add [non-]parametric random residual)

    - linear regression 

    - robust linear regression (M-estimation)

    - ridge/elasticnet/lasso regression (from version >= 0.2.1)

    - CART models

    - Random forest

- Model based, multivariate

    - Imputation based on EM-estimated parameters (from version >= 0.2.1)

    - [missForest](https://CRAN.R-project.org/package=missForest) (from version >= 0.2.1)

- Donor imputation (including various donor pool specifications)

  - k-nearest neigbour (based on [gower](https://cran.r-project.org/package=gower)'s distance)

  - sequential hotdeck (LOCF, NOCB)

  - random hotdeck

  - Predictive mean matching

- Other

  - (groupwise) median imputation (optional random residual)

  - Proxy imputation (copy from other variable) 

### Installation

To install simputation and all packages needed to support various imputation

models do the following.

```r

install.packages("simputation", dependencies=TRUE)

```

To install the development version.

```{bash}

git clone https://github.com/markvanderloo/simputation

make install

```

### Example usage

Create some data suffering from missings

```r

library(simputation) # current package

dat <- iris

# empty a few fields

dat[1:3,1] <- dat[3:7,2] <- dat[8:10,5] <- NA

head(dat,10)

```

Now impute `Sepal.Length` and `Sepal.Width` by regression on `Petal.Length` and `Species`, and impute `Species` using a CART model, that uses all other variables (including the imputed variables in this case).

```r

dat |>

  impute_lm(Sepal.Length + Sepal.Width ~ Petal.Length + Species) |>

  impute_cart(Species ~ .) |> # use all variables except 'Species' as predictor

  head(10)

```

### Materials

- The introductory [vignette](https://cran.r-project.org/web/packages/simputation/vignettes/intro.html)

- [slides](https://markvanderloo.eu/files/share/loo2017easy.pdf) from my [useR2017](https://user2017.brussels/) talk.