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


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Documentation for package ‘capybara’ version 1.0.1

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