Package: GPvam 3.3-0

GPvam: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling

An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, estimates generalized, reduced generalized, variable, complete, and zero persistence models by maximum likelihood or restricted maximum likelihood (the default). These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects; see Mariano et al. (2010) <doi:10.3102/1076998609346967>.

Authors:Andrew Karl [cre, aut], Yan Yang [aut], Sharon Lohr [aut]

GPvam_3.3-0.tar.gz
GPvam_3.3-0.zip(r-4.7-x86_64)GPvam_3.3-0.zip(r-4.7-arm64)GPvam_3.3-0.zip(r-4.6-x86_64)GPvam_3.3-0.zip(r-4.6-arm64)GPvam_3.3-0.zip(r-4.5-x86_64)
GPvam_3.3-0.tgz(r-4.6-x86_64)GPvam_3.3-0.tgz(r-4.6-arm64)GPvam_3.3-0.tgz(r-4.5-x86_64)GPvam_3.3-0.tgz(r-4.5-arm64)
GPvam_3.3-0.tar.gz(r-4.7-arm64)GPvam_3.3-0.tar.gz(r-4.7-x86_64)GPvam_3.3-0.tar.gz(r-4.6-arm64)GPvam_3.3-0.tar.gz(r-4.6-x86_64)
GPvam_3.3-0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
GPvam/json (API)

# Install 'GPvam' in R:
install.packages('GPvam', repos = c('https://akarl46556.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 5 scripts 366 downloads 5 exports 24 dependencies

Last updated from:ed89c5ed64. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK251
linux-devel-x86_64OK274
source / vignettesOK167
linux-release-arm64OK284
linux-release-x86_64OK273
macos-release-arm64OK195
macos-release-x86_64OK590
macos-oldrel-arm64OK227
macos-oldrel-x86_64OK488
windows-devel-arm64OK359
windows-devel-x86_64OK225
windows-release-arm64OK350
windows-release-x86_64OK252
windows-oldrel-x86_64OK254
wasm-releaseOK130

Exports:bias.test.customGPvamplot.GPvamprint.GPvamsummary.GPvam

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixnumDerivpatchworkR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr