Package: alpaca
Type: Package
Title: Fit GLM's with High-Dimensional k-Way Fixed Effects
Version: 0.3.2
Authors@R: c(
  person("Amrei", "Stammann", email = "amrei.stammann@hhu.de", role = c("aut", "cre")),
  person("Daniel", "Czarnowske", email = "daniel.czarnowske@hhu.de", role = c("aut"),
          comment = c(ORCID = "0000-0002-0030-929X")))
Description: Provides a routine to concentrate out factors with many levels during the
  optimization of the log-likelihood function of the corresponding generalized linear model (glm).
  The package is based on the algorithm proposed by Stammann (2018) <arXiv:1707.01815> and is
  restricted to glm's that are based on maximum likelihood estimation and non-linear. It also offers
  an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and 
  includes robust and multi-way clustered standard errors. Further the package provides analytical 
  bias corrections for binary choice models (logit and probit) derived by Fernandez-Val 
  and Weidner (2016) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2019).
License: GPL-3
Depends: R (>= 3.1.0)
Imports: data.table, Formula, MASS, Rcpp, stats, utils
LinkingTo: Rcpp, RcppArmadillo
URL: https://github.com/amrei-stammann/alpaca
BugReports: https://github.com/amrei-stammann/alpaca/issues
RoxygenNote: 7.0.2
Suggests: bife, car, knitr, lfe
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-01-12 16:08:52 UTC; Amrei
Author: Amrei Stammann [aut, cre],
  Daniel Czarnowske [aut] (<https://orcid.org/0000-0002-0030-929X>)
Maintainer: Amrei Stammann <amrei.stammann@hhu.de>
Repository: CRAN
Date/Publication: 2020-01-12 16:30:03 UTC
Built: R 3.6.3; x86_64-w64-mingw32; 2020-08-05 03:20:27 UTC; windows
Archs: i386, x64
