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 |
Documentation:
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