alpaca-package |
alpaca: A package for fitting glm's with high-dimensional k-way fixed effects |

biasCorr |
Asymptotic bias correction after fitting binary choice models with a one-/two-/three-way error component |

coef.APEs |
Extract estimates of average partial effects |

coef.feglm |
Extract estimates of structural parameters |

coef.summary.APEs |
Extract coefficient matrix for average partial effects |

coef.summary.feglm |
Extract coefficient matrix for structural parameters |

feglm |
Efficiently fit glm's with high-dimensional k-way fixed effects |

feglm.control |
Set 'feglm' Control Parameters |

feglm.nb |
Efficiently fit negative binomial glm's with high-dimensional k-way fixed effects |

feglmControl |
Set 'feglm' Control Parameters |

fitted.feglm |
Extract 'feglm' fitted values |

getAPEs |
Compute average partial effects after fitting binary choice models with a one-/two-/three-way error component |

getFEs |
Efficiently recover estimates of the fixed effects after fitting 'feglm' |

predict.feglm |
Predict method for 'feglm' fits |

print.APEs |
Print 'APEs' |

print.feglm |
Print 'feglm' |

print.summary.APEs |
Print 'summary.APEs' |

print.summary.feglm |
Print 'summary.feglm' |

simGLM |
Generate an artificial data set for some GLM's with two-way fixed effects |

summary.APEs |
Summarizing models of class 'APEs' |

summary.feglm |
Summarizing models of class 'feglm' |

vcov.APEs |
Compute covariance matrix after estimating 'APEs' |

vcov.feglm |
Compute covariance matrix after fitting 'feglm' |