Package: bife 0.7.2

bife: Binary Choice Models with Fixed Effects

Estimates fixed effects binary choice models (logit and probit) with potentially many individual fixed effects and computes average partial effects. Incidental parameter bias can be reduced with an asymptotic bias correction proposed by Fernandez-Val (2009) <doi:10.1016/j.jeconom.2009.02.007>.

Authors:Amrei Stammann [aut, cre], Daniel Czarnowske [aut], Florian Heiss [aut], Daniel McFadden [ctb]

bife_0.7.2.tar.gz
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bife.pdf |bife.html
bife/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/amrei-stammann/bife/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • psid - Female labor force participation

On CRAN:

5 exports 8 stars 1.64 score 4 dependencies 1 mentions 54 scripts 2.1k downloads

Last updated 2 years agofrom:1f1ffc00a7. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 12 2024
R-4.5-win-x86_64NOTESep 12 2024
R-4.5-linux-x86_64NOTESep 12 2024
R-4.4-win-x86_64NOTESep 12 2024
R-4.4-mac-x86_64NOTESep 12 2024
R-4.4-mac-aarch64NOTESep 12 2024
R-4.3-win-x86_64NOTESep 12 2024
R-4.3-mac-x86_64NOTESep 12 2024
R-4.3-mac-aarch64NOTESep 12 2024

Exports:apeff_bifebias_corrbifebife_controlget_APEs

Dependencies:data.tableFormulaRcppRcppArmadillo

How to use bife

Rendered fromhowto.Rmdusingknitr::rmarkdownon Sep 12 2024.

Last update: 2022-09-19
Started: 2019-05-24