Package: alpaca 0.3.4

Amrei Stammann

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) <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) <arxiv:2004.12655>.

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

alpaca_0.3.4.tar.gz
alpaca_0.3.4.tar.gz(r-4.5-noble)alpaca_0.3.4.tar.gz(r-4.4-noble)
alpaca_0.3.4.tgz(r-4.4-emscripten)alpaca_0.3.4.tgz(r-4.3-emscripten)
alpaca.pdf |alpaca.html
alpaca/json (API)
NEWS

# Install 'alpaca' in R:
install.packages('alpaca', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/amrei-stammann/alpaca/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

2.45 score 1.4k downloads 8 exports 5 dependencies

Last updated 3 years agofrom:4fc8079b7c. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 29 2025
R-4.5-linux-x86_64NOTEMar 29 2025
R-4.4-linux-x86_64NOTEMar 29 2025

Exports:biasCorrfeglmfeglm.controlfeglm.nbfeglmControlgetAPEsgetFEssimGLM

Dependencies:data.tableFormulaMASSRcppRcppArmadillo

Estimating the intensive and extensive margin of trade

Rendered fromtrade.Rmdusingknitr::rmarkdownon Mar 29 2025.

Last update: 2022-08-10
Started: 2020-01-12

How to use alpaca

Rendered fromhowto.Rmdusingknitr::rmarkdownon Mar 29 2025.

Last update: 2022-08-10
Started: 2019-05-14

Citation

To cite alpaca in publications use:

Stammann, Amrei (2018). Fast and Feasible Estimation of Generalized Linear Models with High-Dimensional k-way Fixed Effects. ArXiv e-prints.

To cite the bias corrections of Fernández-Val and Weidner (2016), i. e. biasCorr() for a classical panel structure, in publications use:

Fernández-Val, Iván and Martin Weidner (2016). Individual and time effects in nonlinear panel models with large N, T. Journal of Econometrics 192(1), 291-312.

To cite the bias corrections of Hinz, Stammann, and Wanner (2020), i. e. biasCorr() for a network panel structure, in publications use:

Hinz, Julian, Amrei Stammann, and Joschka Wanner (2020). State Dependence and Unobserved Heterogeneity in the Extensive Margin of Trade. ArXiv e-prints.

Corresponding BibTeX entries:

  @Article{,
    title = {Fast and Feasible Estimation of Generalized Linear Models
      with High-Dimensional k-way Fixed Effects},
    author = {Amrei Stammann},
    journal = {ArXiv e-prints},
    year = {2018},
    url = {https://arxiv.org/pdf/1707.01815.pdf},
    encoding = {UTF-8},
  }
  @Article{,
    title = {Individual and time effects in nonlinear panel models with
      large N, T},
    author = {Iván Fernández-Val and Martin Weidner},
    journal = {Journal of Econometrics},
    volume = {192},
    number = {1},
    pages = {291--312},
    year = {2016},
    doi = {10.1016/j.jeconom.2015.12.014},
    url =
      {https://www.sciencedirect.com/science/article/pii/S0304407615002997},
    encoding = {UTF-8},
  }
  @Article{,
    title = {State Dependence and Unobserved Heterogeneity in the
      Extensive Margin of Trade},
    author = {Julian Hinz and Amrei Stammann and Joschka Wanner},
    journal = {ArXiv e-prints},
    year = {2020},
    url = {https://arxiv.org/pdf/2004.12655.pdf},
    encoding = {UTF-8},
  }