gppm: Gaussian Process Panel Modeling

Provides an implementation of Gaussian process panel modeling (GPPM). GPPM is described in Karch (2016; <doi:10.18452/17641>) and Karch, Brandmaier & Voelkle (2018; <doi:10.17605/OSF.IO/KVW5Y>). 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.

Version: 0.2.0
Depends: R (≥ 3.1.0), Rcpp (≥ 0.12.17)
Imports: rstan (≥ 2.17.3), ggplot2 (≥ 2.2.1), MASS (≥ 7.3-49), ggthemes (≥ 3.5.0), mvtnorm (≥ 1.0-8), stats, methods
Suggests: testthat (≥ 2.0.0), knitr (≥ 1.20), rmarkdown (≥ 1.10), roxygen2 (≥ 6.0.1)
Published: 2018-07-05
Author: Julian D. Karch [aut, cre, cph]
Maintainer: Julian D. Karch <j.d.karch at fsw.leidenuniv.nl>
BugReports: https://github.com/karchjd/gppm/issues
License: GPL-3 | file LICENSE
URL: https://github.com/karchjd/gppm
NeedsCompilation: no
CRAN checks: gppm results

Downloads:

Reference manual: gppm.pdf
Package source: gppm_0.2.0.tar.gz
Windows binaries: r-devel: gppm_0.2.0.zip, r-devel-gcc8: gppm_0.2.0.zip, r-release: gppm_0.2.0.zip, r-oldrel: gppm_0.2.0.zip
OS X binaries: r-release: gppm_0.2.0.tgz, r-oldrel: gppm_0.2.0.tgz

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