R: Fit GLM's with High-Dimensional k-Way Fixed Effects

# Fit GLM's with High-Dimensional k-Way Fixed Effects

## Documentation for package ‘alpaca’ version 0.3.5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

alpaca-package | alpaca: A package for fitting glm's with high-dimensional k-way fixed effects
biasCorr | Asymptotic bias correction after fitting binary choice models with a one-/two-/three-way error component
coef.APEs | Extract estimates of average partial effects
coef.feglm | Extract estimates of structural parameters
coef.summary.APEs | Extract coefficient matrix for average partial effects
coef.summary.feglm | Extract coefficient matrix for structural parameters
feglm | Efficiently fit glm's with high-dimensional k-way fixed effects
feglm.control | Set 'feglm' Control Parameters
feglm.nb | Efficiently fit negative binomial glm's with high-dimensional k-way fixed effects
feglmControl | Set 'feglm' Control Parameters
fitted.feglm | Extract 'feglm' fitted values
getAPEs | Compute average partial effects after fitting binary choice models with a one-/two-/three-way error component
getFEs | Efficiently recover estimates of the fixed effects after fitting 'feglm'
predict.feglm | Predict method for 'feglm' fits
print.APEs | Print 'APEs'
print.feglm | Print 'feglm'
print.summary.APEs | Print 'summary.APEs'
print.summary.feglm | Print 'summary.feglm'
simGLM | Generate an artificial data set for some GLM's with two-way fixed effects
summary.APEs | Summarizing models of class 'APEs'
summary.feglm | Summarizing models of class 'feglm'
vcov.APEs | Compute covariance matrix after estimating 'APEs'
vcov.feglm | Compute covariance matrix after fitting 'feglm'