Package: FEprovideR 1.1

Michael Kleinsasser

FEprovideR: Fixed Effects Logistic Model with High-Dimensional Parameters

A structured profile likelihood algorithm for the logistic fixed effects model and an approximate expectation maximization (EM) algorithm for the logistic mixed effects model. Based on He, K., Kalbfleisch, J.D., Li, Y. and Li, Y. (2013) <doi:10.1007/s10985-013-9264-6>.

Authors:Kevin He [aut], Wenbo Wu [aut], Michael Kleinsasser [cre]

FEprovideR_1.1.tar.gz
FEprovideR_1.1.zip(r-4.7)FEprovideR_1.1.zip(r-4.6)FEprovideR_1.1.zip(r-4.5)
FEprovideR_1.1.tgz(r-4.6-any)FEprovideR_1.1.tgz(r-4.5-any)
FEprovideR_1.1.tar.gz(r-4.7-any)FEprovideR_1.1.tar.gz(r-4.6-any)
FEprovideR_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
FEprovideR/json (API)

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

Bug tracker:https://github.com/umich-biostatistics/feprovider/issues

Datasets:
  • hospital - Simulated readmissions data for 500 hospitals
  • hospital_prepared - Prepared version of simulated readmissions data for 500 hospitals

On CRAN:

Conda:

2.70 score 1 stars 1 scripts 295 downloads 5 exports 20 dependencies

Last updated from:36d01cf8e5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK139
source / vignettesOK187
linux-release-x86_64OK137
macos-release-arm64OK101
macos-oldrel-arm64OK111
windows-develOK91
windows-releaseOK92
windows-oldrelOK96
wasm-releaseOK99

Exports:confint.fe.provfe.data.prepfe.provfunnel.SRRtest.fe.prov

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglatticelifecycleMatrixpoibinR6RColorBrewerrlangS7scalesvctrsviridisLitewithr