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gppm
View on CRAN: Click
here
Download and install gppm package within the R console
Install from CRAN:
install.packages("gppm")
Install from Github:
library("remotes")
install_github("cran/gppm") Install by package version:
library("remotes")
install_version("gppm", "0.2.0") Attach the package and use:
library("gppm")
Maintained by
Julian D. Karch
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-07-05
Latest Update: 2025-08-25
Description:
Provides an implementation of Gaussian process panel modeling GPPM.GPPM is described in Karch 2016 DOI10.1845217641 and Karch Brandmaier Voelkle 2018 DOI10.17605OSF.IOKVW5Y.Essentially GPPM is Gaussian process based modeling of longitudinal panel data.gppm also supports regular Gaussian process regression with a focus on flexible model specification and multi-task learning.
How to cite:
Julian D. Karch (2018). gppm: Gaussian Process Panel Modeling. R package version 0.2.0, https://cran.r-project.org/web/packages/gppm. Accessed 29 Oct. 2026.
Previous versions and publish date:
Other packages that cited gppm R package
View gppm citation profile
Other R packages that gppm depends,
imports, suggests or enhances
Functions, R codes and Examples using
the gppm R package
Some associated functions: SE . accuracy . coef.GPPM . confint.GPPM . covf . createLeavePersonsOutFolds . crossvalidate . datas . demoLGCM . fit.GPPM . fit . fitted.GPPM . getIntern . gppm . gppmControl . logLik.GPPM . maxnObs . meanf . nObs . nPars . nPers . nPreds . parEsts . pars . plot.GPPMPred . plot.LongData . predict.GPPM . preds . simulate.GPPM . summary.GPPM . trueParas . vcov.GPPM .
Some associated R codes: FitRes.R . GPPM.R . GPPMControl.R . LongData.R . ParsedModel.R . StanData.R . cross_validation.R . data.R . extractors.R . fit.R . plotLong.R . predict.R . simulate.R . summary.R . toStan.R . Full gppm package functions and examples
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