Package: geeVerse 0.2.1

geeVerse: A Comprehensive Analysis of High Dimensional Longitudinal Data

To provide a comprehensive analysis of high dimensional longitudinal data,this package provides analysis for any combination of 1) simultaneous variable selection and estimation, 2) mean regression or quantile regression for heterogeneous data, 3) cross-sectional or longitudinal data, 4) balanced or imbalanced data, 5) moderate, high or even ultra-high dimensional data, via computationally efficient implementations of penalized generalized estimating equations.

Authors:Tianhai Zu [aut, cre], Brittany Green [aut, ctb], Yan Yu [aut, ctb]

geeVerse_0.2.1.tar.gz
geeVerse_0.2.1.zip(r-4.5)geeVerse_0.2.1.zip(r-4.4)geeVerse_0.2.1.zip(r-4.3)
geeVerse_0.2.1.tgz(r-4.4-x86_64)geeVerse_0.2.1.tgz(r-4.4-arm64)geeVerse_0.2.1.tgz(r-4.3-x86_64)geeVerse_0.2.1.tgz(r-4.3-arm64)
geeVerse_0.2.1.tar.gz(r-4.5-noble)geeVerse_0.2.1.tar.gz(r-4.4-noble)
geeVerse_0.2.1.tgz(r-4.4-emscripten)geeVerse_0.2.1.tgz(r-4.3-emscripten)
geeVerse.pdf |geeVerse.html
geeVerse/json (API)

# Install 'geeVerse' in R:
install.packages('geeVerse', repos = c('https://zzz1990771.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/zzz1990771/geeverse/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • simuGene - A Simulated Genetic Data from HapGen2
  • yeastG1 - A Subset of Yeast Cell Cycle Gene Expression Data

On CRAN:

3.74 score 11 scripts 228 downloads 6 exports 14 dependencies

Last updated 4 months agofrom:4d5d3650ea. Checks:OK: 1 ERROR: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-win-x86_64ERROROct 10 2024
R-4.5-linux-x86_64ERROROct 10 2024
R-4.4-win-x86_64ERROROct 10 2024
R-4.4-mac-x86_64ERROROct 10 2024
R-4.4-mac-aarch64ERROROct 10 2024
R-4.3-win-x86_64ERROROct 10 2024
R-4.3-mac-x86_64ERROROct 10 2024
R-4.3-mac-aarch64ERROROct 10 2024

Exports:CVfitgenerateDataPGEEqpgeeqpgee.estSiga_cov

Dependencies:codetoolsdoParallelforeachiteratorslatticeMASSMatrixMatrixModelsmvtnormquantregRcppRcppEigenSparseMsurvival