Package: GPvam 3.1-2

Andrew Karl

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>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. 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.

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

GPvam_3.1-2.tar.gz
GPvam_3.1-2.tar.gz(r-4.5-noble)GPvam_3.1-2.tar.gz(r-4.4-noble)
GPvam_3.1-2.tgz(r-4.4-emscripten)GPvam_3.1-2.tgz(r-4.3-emscripten)
GPvam.pdf |GPvam.html
GPvam/json (API)
NEWS

# Install 'GPvam' in R:
install.packages('GPvam', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

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

1.48 score 5 scripts 408 downloads 5 exports 32 dependencies

Last updated 20 days agofrom:c7b60ef19c. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-linux-x86_64OKNov 19 2024

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

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmenumDerivpatchworkpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalestibbleutf8vctrsviridisLitewithr