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alpaca
View on CRAN: Click
here
Download and install alpaca package within the R console
Install from CRAN:
install.packages("alpaca")
Install from Github:
library("remotes")
install_github("cran/alpaca") Install by package version:
library("remotes")
install_version("alpaca", "0.3.5") Attach the package and use:
library("alpaca")
Maintained by
Amrei Stammann
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All associated links for this package
First Published: 2018-07-31
Latest Update: 2022-08-10
Description:
Provides a routine to partial 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 described in Stammann (2018) and is restricted to glm's that are based on maximum likelihood estimation and nonlinear. 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 derived by Fernandez-Val and Weidner (2016) and Hinz, Stammann, and Wanner (2020) .
How to cite:
Amrei Stammann (2018). alpaca: Fit GLM's with High-Dimensional k-Way Fixed Effects. R package version 0.3.5, https://cran.r-project.org/web/packages/alpaca. Accessed 07 Oct. 2026.
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imports, suggests or enhances
Complete documentation for alpaca
Functions, R codes and Examples using
the alpaca R package
Some associated functions: alpaca-package . biasCorr . coef.APEs . coef.feglm . coef.summary.APEs . coef.summary.feglm . feglm.nb . feglm . feglmControl . fitted.feglm . getAPEs . getFEs . predict.feglm . print.APEs . print.feglm . print.summary.APEs . print.summary.feglm . simGLM . summary.APEs . summary.feglm . vcov.APEs . vcov.feglm .
Some associated R codes: RcppExports.R . alpaca.R . biasCorr.R . feglm.R . feglm.nb.R . feglmControl.R . generics.R . getAPEs.R . getFEs.R . internals.R . simGLM.R . Full alpaca package functions and examples
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