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

alpaca | alpaca: A package for fitting glm's with high-dimensional... |

alpaca-package | alpaca: A package for fitting glm's with high-dimensional... |

biasCorr | Asymptotic bias correction after fitting binary choice models... |

coef.APEs | Extract estimates of average partial effects |

coef.feglm | Extract estimates of structural parameters |

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

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

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

feglm.control | Set 'feglm' Control Parameters |

feglmControl | Set 'feglm' Control Parameters |

feglm.nb | Efficiently fit negative binomial glm's with high-dimensional... |

fitted.feglm | Extract 'feglm' fitted values |

getAPEs | Compute average partial effects after fitting binary choice... |

getFEs | Efficiently recover estimates of the fixed effects after... |

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... |

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

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

vcov.feglm | Extract estimates of the covariance matrix |

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