alpaca
Fit 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) <doi:10.48550/arXiv.1707.01815> 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) <doi:10.1016/j.jeconom.2015.12.014> and Hinz, Stammann, and Wanner (2020) <doi:10.48550/arXiv.2004.12655>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.3.5 |
rolling linux/jammy R-4.5 | alpaca_0.3.5.tar.gz |
223.2 KiB |
0.3.5 |
rolling linux/noble R-4.5 | alpaca_0.3.5.tar.gz |
225.2 KiB |
0.3.5 |
rolling source/ R- | alpaca_0.3.5.tar.gz |
78.4 KiB |
0.3.5 |
latest linux/jammy R-4.5 | alpaca_0.3.5.tar.gz |
223.2 KiB |
0.3.5 |
latest linux/noble R-4.5 | alpaca_0.3.5.tar.gz |
225.2 KiB |
0.3.5 |
latest source/ R- | alpaca_0.3.5.tar.gz |
78.4 KiB |
0.3.5 |
2026-04-26 source/ R- | alpaca_0.3.5.tar.gz |
78.4 KiB |
0.3.5 |
2026-04-23 source/ R- | alpaca_0.3.5.tar.gz |
78.4 KiB |
0.3.5 |
2026-04-09 windows/windows R-4.5 | alpaca_0.3.5.zip |
553.1 KiB |
0.3.4 |
2025-04-20 source/ R- | alpaca_0.3.4.tar.gz |
67.4 KiB |