growcurves: Bayesian Semi and Nonparametric Growth Curve Models that Additionally Include Multiple Membership Random Effects

Employs a non-parametric formulation for by-subject random effect parameters to borrow strength over a constrained number of repeated measurement waves in a fashion that permits multiple effects per subject. One class of models employs a Dirichlet process (DP) prior for the subject random effects and includes an additional set of random effects that utilize a different grouping factor and are mapped back to clients through a multiple membership weight matrix; e.g. treatment(s) exposure or dosage. A second class of models employs a dependent DP (DDP) prior for the subject random effects that directly incorporates the multiple membership pattern.

Depends: R (≥ 3.2.2), Rcpp (≥ 0.11.6)
Imports: reshape2 (≥ 1.2.1), Formula (≥ 1.0-0), ggplot2 (≥ 1.0.1)
LinkingTo: Rcpp (≥ 0.11.6), RcppArmadillo (≥ 0.5.000)
Suggests: testthat (≥ 0.9.1)
Published: 2016-12-21
Author: Terrance Savitsky
Maintainer: Terrance Savitsky <tds151 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: growcurves citation info
Materials: NEWS
In views: Bayesian
CRAN checks: growcurves results


Reference manual: growcurves.pdf
Package source: growcurves_0.2.4.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: growcurves_0.2.4.1.tgz, r-oldrel: growcurves_0.2.4.1.tgz
Old sources: growcurves archive


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