Package: GPvam 3.2-0
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>, 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:
GPvam_3.2-0.tar.gz
GPvam_3.2-0.zip(r-4.7)GPvam_3.2-0.zip(r-4.6)GPvam_3.2-0.zip(r-4.5)
GPvam_3.2-0.tgz(r-4.6-x86_64)GPvam_3.2-0.tgz(r-4.6-arm64)GPvam_3.2-0.tgz(r-4.5-x86_64)GPvam_3.2-0.tgz(r-4.5-arm64)
GPvam_3.2-0.tar.gz(r-4.7-arm64)GPvam_3.2-0.tar.gz(r-4.7-x86_64)GPvam_3.2-0.tar.gz(r-4.6-arm64)GPvam_3.2-0.tar.gz(r-4.6-x86_64)
GPvam_3.2-0.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')) |
- GPvam.benchmark - Benchmarks of the program using simulated data.
- vam_data - Simulated Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b9b7bd2f49. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 157 | ||
| linux-devel-x86_64 | OK | 156 | ||
| source / vignettes | OK | 152 | ||
| linux-release-arm64 | OK | 152 | ||
| linux-release-x86_64 | OK | 152 | ||
| macos-release-arm64 | OK | 100 | ||
| macos-release-x86_64 | OK | 310 | ||
| macos-oldrel-arm64 | OK | 106 | ||
| macos-oldrel-x86_64 | OK | 203 | ||
| windows-devel | OK | 136 | ||
| windows-release | OK | 132 | ||
| windows-oldrel | OK | 202 | ||
| wasm-release | OK | 131 |
Exports:bias.test.customGPvamplot.GPvamprint.GPvamsummary.GPvam
Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMASSMatrixnumDerivpatchworkR6RColorBrewerRcppRcppArmadillorlangS7scalesvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling | GPvam-package |
| Permutation Tests for Fixed Effects Bias Assessment | bias.test.custom |
| Internal G-side effects function | GP.csh |
| Internal R-side effects function | GP.un |
| Fitting the Generalized and Variable Persistence Models | GPvam |
| Benchmarks of the program using simulated data. | GPvam.benchmark |
| Plot method for GPvam | plot.GPvam |
| print.GPvam print.summary.GPvam | |
| Internal R-side effects function for reduced GP model | rGP.un |
| Summary | summary.GPvam |
| Simulated Data | vam_data |
| Internal R-side effects function for the variable persistence model. | VP.CP.ZP.un |
