Package: geer 0.1.1
geer: Bias-Reduced and Penalized Generalized Estimating Equations
Fits marginal regression models for repeated or clustered responses using generalized estimating equations (GEE). Provides ordinary GEE estimators, bias-reduced and bias-corrected GEE estimators, and Jeffreys-type penalized GEE estimators for binary, count and continuous responses. Methods are described in Touloumis (2026a) <doi:10.48550/arXiv.2606.16043> and Touloumis (2026b) <doi:10.48550/arXiv.2606.16058>.
Authors:
geer_0.1.1.tar.gz
geer_0.1.1.zip(r-4.7-x86_64)geer_0.1.1.zip(r-4.7-arm64)geer_0.1.1.zip(r-4.6-x86_64)geer_0.1.1.zip(r-4.6-arm64)geer_0.1.1.zip(r-4.5-x86_64)
geer_0.1.1.tgz(r-4.6-x86_64)geer_0.1.1.tgz(r-4.6-arm64)geer_0.1.1.tgz(r-4.5-x86_64)geer_0.1.1.tgz(r-4.5-arm64)
geer_0.1.1.tar.gz(r-4.7-arm64)geer_0.1.1.tar.gz(r-4.7-x86_64)geer_0.1.1.tar.gz(r-4.6-arm64)geer_0.1.1.tar.gz(r-4.6-x86_64)
geer_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
geer/json (API)
| # Install 'geer' in R: |
| install.packages('geer', repos = c('https://anestistouloumis.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/anestistouloumis/geer/issues
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Last updated from:e5b1ac9e95. Checks:3 ERROR, 12 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | ERROR | 140 | ||
| linux-devel-x86_64 | ERROR | 189 | ||
| source / vignettes | OK | 263 | ||
| linux-release-arm64 | OK | 180 | ||
| linux-release-x86_64 | OK | 225 | ||
| macos-release-arm64 | OK | 222 | ||
| macos-release-x86_64 | OK | 425 | ||
| macos-oldrel-arm64 | OK | 185 | ||
| macos-oldrel-x86_64 | OK | 557 | ||
| windows-devel-arm64 | ERROR | 407 | ||
| windows-devel-x86_64 | OK | 235 | ||
| windows-release-arm64 | OK | 461 | ||
| windows-release-x86_64 | OK | 236 | ||
| windows-oldrel-x86_64 | OK | 251 | ||
| wasm-release | OK | 131 |
Exports:emm_basis.geerfrechet_bounds_corgeecriteriageer_controlgeewageewa_binaryglancemcar_homoscedasticity_testmcar_little_testmcar_logistic_testrecover_data.geerruns_teststep_ptidy
Dependencies:brglm2enrichwithgenericslatticeMASSMatrixnleqslvnnetnumDerivRcppRcppArmadillostatmod