Package: capybara 0.9.0

capybara: Fast and Memory Efficient Fitting of Linear Models with High-Dimensional Fixed Effects

Fast and user-friendly estimation of generalized linear models with multiple fixed effects and cluster the standard errors. The method to obtain the estimated fixed-effects coefficients is based on Stammann (2018) <doi:10.48550/arXiv.1707.01815> and Gaure (2013) <doi:10.1016/j.csda.2013.03.024>.

Authors:Mauricio Vargas Sepulveda [aut, cre]

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capybara.pdf |capybara.html✨
capybara/json (API)
NEWS

# Install 'capybara' in R:

install.packages('capybara', repos = c('https://pachadotdev.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pachadotdev/capybara/issues

Pkgdown site:https://pacha.dev

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

trade_panel - Trade Panel 1986-2006

On CRAN:

cpp11 econometrics linear-models openblas cpp openmp

6.07 score 13 stars 12 exports 34 dependencies

Last updated 9 hours agofrom:fc58c42812. Checks:12 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 25 2025
R-4.5-win-x86_64	OK	Mar 25 2025
R-4.5-mac-x86_64	OK	Mar 25 2025
R-4.5-mac-aarch64	OK	Mar 25 2025
R-4.5-linux-x86_64	OK	Mar 25 2025
R-4.4-win-x86_64	OK	Mar 25 2025
R-4.4-mac-x86_64	OK	Mar 25 2025
R-4.4-mac-aarch64	OK	Mar 25 2025
R-4.4-linux-x86_64	OK	Mar 25 2025
R-4.3-win-x86_64	OK	Mar 25 2025
R-4.3-mac-x86_64	OK	Mar 25 2025
R-4.3-mac-aarch64	OK	Mar 25 2025

Exports:apes augment autoplot bias_corr feglm feglm_control felm fenegbin fepoisson fixed_effects glance tidy

Dependencies:cli colorspace cpp11 cpp11armadillo data.table fansi farver Formula generics ggplot2 glue gtable isoband kendallknight labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig R6 RColorBrewer rlang scales tibble utf8 vctrs viridisLite withr

Poisson Pseudo-Maximum Likelihood (PPML) Model with Cluster-Robust Standard Errors

Rendered fromintro.Rmdusingknitr::rmarkdownon Mar 25 2025.

Last update: 2024-07-06
Started: 2024-07-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Generalized Linear Models (GLMs) with high-dimensional k-way fixed effects	capybara-package capybara
Compute average partial effects after fitting binary choice models with a 1,2,3-way error component	apes
Broom Integration	augment.feglm augment.felm glance.feglm glance.felm tidy.feglm tidy.felm
Autoplot method for feglm objects	autoplot.feglm autoplot.felm
Asymptotic bias correction after fitting binary choice models with a 1,2,3-way error component	bias_corr
GLM fitting with high-dimensional k-way fixed effects	feglm
Set 'feglm' Control Parameters	feglm_control
LM fitting with high-dimensional k-way fixed effects	felm
Negative Binomial model fitting with high-dimensional k-way fixed effects	fenegbin
Poisson model fitting high-dimensional with k-way fixed effects	fepoisson
Recover the estimates of the fixed effects after fitting (G)LMs	fixed_effects
Trade Panel 1986-2006	trade_panel
Covariance matrix for GLMs	vcov.feglm
Covariance matrix for LMs	vcov.felm