Multi-Model Inference

AICc | Second-order Akaike Information Criterion |

arm.glm | Adaptive Regression by Mixing |

BGweights | Bates-Granger minimal variance model weights |

bootWeights | Bootstrap model weights |

coefplot | Plot model coefficients |

cos2weights | Cos-squared model weights |

data-Beetle | Flour beetle mortality data |

data-Cement | Cement hardening data |

data-GPA | Grade Point Average data |

dredge | Automated model selection |

exprApply | Apply a function to calls inside an expression |

get.models | Retrieve models from selection table |

ICs | Various information criteria |

jackknifeWeights | Jackknifed model weights |

loo | Leave-one-out cross-validation |

manip-formula | Manipulate model formulas |

merge.model.selection | Combine model selection tables |

model.avg | Model averaging |

model.sel | model selection table |

model.selection.object | Description of Model Selection Objects |

model-utils | Model utility functions |

MuMIn-package | Multi-model inference |

nested | Identify nested models |

par.avg | Parameter averaging |

pdredge | Automated model selection using parallel computation |

plot.model.selection | Visualize model selection table |

predict.averaging | Predict method for averaged models |

QAIC | Quasi AIC or AICc |

QIC | QIC and quasi-Likelihood for GEE |

r.squaredGLMM | Pseudo-R-squared for Generalized Mixed-Effect models |

r.squaredLR | Likelihood-ratio based pseudo-R-squared |

stackingWeights | Stacking model weights |

std.coef | Standardized model coefficients |

stdize | Standardize data |

subset.model.selection | Subsetting model selection table |

sumofweights | Per-variable sum of model weights |

supported-classes | List of supported models |

updateable | Make a function return updateable result |

Weights | Akaike weights |

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