amrei-stammann / alpaca

An R-package for fitting glm's with high-dimensional k-way fixed effects
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alpaca

Info

An R-package for fitting glm's with high-dimensional k-way fixed effects.

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 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 (2020).

If you have any suggestions for improvements or questions, feel free to contact me.

The package is also available on CRAN.

News

alpaca v0.3.4 (Release Date: 2022-08-10)

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alpaca v0.3.3 (Release Date: 2020-10-30)

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alpaca v0.3.2 (Release Date: 2020-01-12)

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alpaca v0.3.1 (Release Date: 2019-05-24)

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alpaca v0.3 (Release Date: 2019-05-14)

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alpaca v0.2 (Release Date: 2018-07-23)

ATTENTION: Syntax changed slightly. Have a look at the vignettes or help files.

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alpaca v0.1.3 (Release Date: 2018-03-08)

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alpaca v0.1.2 (Release Date: 2018-03-04)

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alpaca v0.1.1 (Release Date: 2018-01-21)

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