capybara0.9.1 package

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

apes

Compute average partial effects after fitting binary choice models wit...

autoplot

Autoplot method for feglm objects

bias_corr

Asymptotic bias correction after fitting binary choice models with a 1...

broom

Broom Integration

capybara-package

Generalized Linear Models (GLMs) with high-dimensional k-way fixed eff...

feglm_control

Set feglm Control Parameters

feglm

GLM fitting with high-dimensional k-way fixed effects

felm

LM fitting with high-dimensional k-way fixed effects

fenegbin

Negative Binomial model fitting with high-dimensional k-way fixed effe...

fepoisson

Poisson model fitting high-dimensional with k-way fixed effects

fixed_effects

Recover the estimates of the fixed effects after fitting (G)LMs

reexports

Objects exported from other packages

vcov.feglm

Covariance matrix for GLMs

vcov.felm

Covariance matrix for LMs

Download source packageRead PDF manual

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>.

  • Maintainer: Mauricio Vargas Sepulveda
  • License: Apache License (>= 2)
  • Last published: 2025-03-26

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