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lgpr

R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.

Getting started

See overview, tutorials, vignettes and documentation at https://jtimonen.github.io/lgpr-usage/index.html.

Requirements

• The package should work on all major operating systems.
• R 3.4 or later is required, R 4.0.2 or later is recommended

Installing from CRAN

• The latest released version that is available from CRAN can be installed simply via

install.packages("lgpr")

Installing 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).

Installing from source

• The latest released version (which might not be in CRAN yet) can be installed via

install.packages('devtools') # if you don't have devtools already
devtools::install_github('jtimonen/lgpr', build_vignettes = TRUE)

• The latest development version can be installed via

devtools::install_github('jtimonen/lgpr', ref = "develop")

Github installations are source installations (they require a C++ compiler).

• If you have trouble installing the dependency rstan, see these instructions
• Installing from source requires that you have your toolchain setup properly. See the instructions for:
  • Linux
  • Windows
  • Mac

Real data and reproducing the experiments

For code to reproduce the experiments of our manuscript see https://github.com/jtimonen/lgpr-usage. Preprocessed longitudinal proteomics data is also provided there. See also the built-in read_proteomics_data() function.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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