{"id":32203174,"url":"https://github.com/jtimonen/lgpr","last_synced_at":"2026-02-21T18:04:23.409Z","repository":{"id":54973332,"uuid":"209037141","full_name":"jtimonen/lgpr","owner":"jtimonen","description":"R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes.  Contains functionality for inferring covariate effects and assessing covariate relevances. 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Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.\n\n\u003e [!NOTE]\n\u003e Using this package is computationally viable if your data set has maybe less than 300 observations. But the much more scalable [lgpr2](https://github.com/jtimonen/lgpr2) package has been released! It is much faster but unfortunately doesn't have all the special modeling features included in this package.\n\n\n## Getting started\nSee overview, tutorials, vignettes and documentation at https://jtimonen.github.io/lgpr-usage/index.html. \n\n## Requirements\n* The package should work on all major operating systems. \n* R 3.4 or later is required, R 4.2 or later is recommended\n\n## Installing from CRAN\n* The latest released version that is available from CRAN can be installed simply via\n\n```r\ninstall.packages(\"lgpr\")\n```\nInstalling from CRAN is probably the easiest option since they might have binaries for your system (so no need to build the package from source yourself).\n\n## Installing from source\n* The latest released version (which might not be in CRAN yet) can be installed via\n\n```r\ninstall.packages('devtools') # if you don't have devtools already\ndevtools::install_github('jtimonen/lgpr', build_vignettes = TRUE)\n```\n\n* The latest development version can be installed via\n\n```r\ndevtools::install_github('jtimonen/lgpr', ref = \"develop\")\n``` \nGithub installations are source installations (they require a C++ compiler).\n\n* If you have trouble installing the dependency [rstan](https://mc-stan.org/rstan/), see [these instructions](https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started)\n* Installing from source requires that you have your toolchain setup properly.\nSee the instructions for:\n  - [Linux](https://github.com/stan-dev/rstan/wiki/Configuring-C-Toolchain-for-Linux)\n  - [Windows](https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Windows)\n  - [Mac](https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Mac)\n\n## Using R \u003c 4.2\n\nIf you are using `R` version 4.1 or earlier, you can get an error \n```\ncc1plus.exe: out of memory allocating 65536 bytes\nmake: *** [C:/PROGRA~1/R/R-40~1.2/etc/i386/Makeconf:227: stanExports_lgp_latent.o] Error 1\n```\nbecause both 64-bit and 32-bit versions of the package are getting installed. To disable this and resolve error,\nugrade to latest R or install the version that has `Biarch: false` by\n\n```r\ndevtools::install_github('jtimonen/lgpr', ref = \"no-biarch\")\n``` \n\n## Real data and reproducing the experiments\nFor code to reproduce the experiments of our manuscript see https://github.com/jtimonen/lgpr-usage. Preprocessed longitudinal proteomics\ndata is also provided there. See also the built-in `read_proteomics_data()` function.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjtimonen%2Flgpr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjtimonen%2Flgpr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjtimonen%2Flgpr/lists"}