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

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) 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) and Hinz, Stammann, and Wanner (2019).


Reference manual

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0.3.2 by Amrei Stammann, 9 months ago

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Authors: Amrei Stammann [aut, cre] , Daniel Czarnowske [aut]

Documentation:   PDF Manual  

Task views: Econometrics

GPL-3 license

Imports data.table, Formula, MASS, Rcpp, stats, utils

Suggests bife, car, knitr, lfe

Linking to Rcpp, RcppArmadillo

Suggested by bife, lfe.

Enhanced by texreg.

See at CRAN