Package: GPvam 3.4-0
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>, 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:
GPvam_3.4-0.tar.gz
GPvam_3.4-0.zip(r-4.7-x86_64)GPvam_3.4-0.zip(r-4.7-arm64)GPvam_3.4-0.zip(r-4.6-x86_64)GPvam_3.4-0.zip(r-4.6-arm64)
GPvam_3.4-0.tar.gz(r-4.7-arm64)GPvam_3.4-0.tar.gz(r-4.7-x86_64)GPvam_3.4-0.tar.gz(r-4.6-arm64)GPvam_3.4-0.tar.gz(r-4.6-x86_64)
GPvam_3.4-0.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://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- GPvam.benchmark - Historical Runtime and Memory Benchmarks
- vam_data - Simulated Value-Added Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:9b16f37eb1. Checks:10 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 343 | ||
| linux-devel-x86_64 | OK | 353 | ||
| source / vignettes | OK | 196 | ||
| linux-release-arm64 | OK | 295 | ||
| linux-release-x86_64 | OK | 451 | ||
| windows-devel-arm64 | OK | 466 | ||
| windows-devel-x86_64 | OK | 430 | ||
| windows-release-arm64 | OK | 473 | ||
| windows-release-x86_64 | OK | 377 | ||
| wasm-release | OK | 104 |
Exports:bias.test.customGPvamplot.GPvamprint.GPvamsimulate_biassummary.GPvam
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixnumDerivpatchworkR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Maximum Likelihood Estimation of Multiple Membership Mixed Models | GPvam-package |
| Inspect Fixed-Effect Alignment with a Permutation Diagnostic | bias.test.custom |
| Fit a Generalized or Variable Persistence Model | GPvam |
| Extract components of a fitted GPvam model | coef.GPvam fitted.GPvam GPvam-methods logLik.GPvam nobs.GPvam residuals.GPvam vcov.GPvam |
| Historical Runtime and Memory Benchmarks | GPvam.benchmark |
| Plot Teacher Effects and Residuals from a GPvam Model | plot.GPvam |
| Print a Fitted GPvam Model | print.GPvam print.summary.GPvam |
| Print a GPvam response-refit simulation | print.GPvam_simulation |
| Response-refit simulations for a fitted GPvam model | simulate_bias |
| Summarize a Fitted GPvam Model | summary.GPvam |
| Simulated Value-Added Data | vam_data |