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lgpr: Longitudinal Gaussian Process Regression

Interpretable nonparametric modeling of longitudinal data using additive Gaussian process regression. Contains functionality for inferring covariate effects and assessing covariate relevances. Models are specified using a convenient formula syntax, and can include shared, group-specific, non-stationary, heterogeneous and temporally uncertain effects. Bayesian inference for model parameters is performed using 'Stan'. The modeling approach and methods are described in detail in Timonen et al. (2021) <doi:10.1093/bioinformatics/btab021>.

Version: 1.2.4
Depends: R (≥ 3.4.0), methods
Imports: Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.2), RCurl (≥ 1.98), rstan (≥ 2.26.0), rstantools (≥ 2.3.1), bayesplot (≥ 1.7.0), MASS (≥ 7.3-50), stats (≥ 3.4), ggplot2 (≥ 3.1.0), gridExtra (≥ 0.3.0)
LinkingTo: BH (≥ 1.75.0-0), Rcpp (≥ 1.0.6), RcppEigen (≥ 0.3.3.9.1), RcppParallel (≥ 5.0.2), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: knitr, rmarkdown, testthat, covr
Published: 2023-09-24
DOI: 10.32614/CRAN.package.lgpr
Author: Juho Timonen ORCID iD [aut, cre], Andrew Johnson [ctb]
Maintainer: Juho Timonen <juho.timonen at iki.fi>
BugReports: https://github.com/jtimonen/lgpr/issues
License: GPL (≥ 3)
URL: https://github.com/jtimonen/lgpr
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: lgpr citation info
Materials: README
CRAN checks: lgpr results

Documentation:

Reference manual: lgpr.pdf
Vignettes: Mathematical description of lgpr models

Downloads:

Package source: lgpr_1.2.4.tar.gz
Windows binaries: r-devel: lgpr_1.2.4.zip, r-release: lgpr_1.2.4.zip, r-oldrel: lgpr_1.2.4.zip
macOS binaries: r-release (arm64): lgpr_1.2.4.tgz, r-oldrel (arm64): lgpr_1.2.4.tgz, r-release (x86_64): lgpr_1.2.4.tgz, r-oldrel (x86_64): lgpr_1.2.4.tgz
Old sources: lgpr archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=lgpr to link to this page.

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.