CARBayes-package |
Spatial Generalised Linear Mixed Models for Areal Unit Data |

CARBayes |
Spatial Generalised Linear Mixed Models for Areal Unit Data |

fitted.CARBayes |
Extract the fitted values from a model. |

highlight.borders |
Creates an sf data.frame object (from the sf package) identifying a subset of borders between neighbouring areas. |

logLik.CARBayes |
Extract the estimated loglikelihood from a fitted model. |

model.matrix.CARBayes |
Extract the model (design) matrix from a model. |

MVS.CARleroux |
Fit a multivariate spatial generalised linear mixed model to data, where the random effects are modelled by a multivariate conditional autoregressive model. |

print.CARBayes |
Print a summary of a fitted CARBayes model to the screen. |

residuals.CARBayes |
Extract the residuals from a model. |

S.CARbym |
Fit a spatial generalised linear mixed model to data, where the random effects have a BYM conditional autoregressive prior. |

S.CARdissimilarity |
Fit a spatial generalised linear mixed model to data, where the random effects have a localised conditional autoregressive prior. |

S.CARleroux |
Fit a spatial generalised linear mixed model to data, where the random effects have a Leroux conditional autoregressive prior. |

S.CARlocalised |
Fit a spatial generalised linear mixed model to data, where a set of spatially smooth random effects are augmented with a piecewise constant intercept process. |

S.CARmultilevel |
Fit a spatial generalised linear mixed model to multi-level areal unit data, where the spatial random effects have a Leroux conditional autoregressive prior. |

S.glm |
Fit a generalised linear model to data. |

S.RAB |
Fit a spatial generalised linear model with anisotropic basis functions to data for computationally efficient localised spatial smoothing, where the parameters are estimated by penalised maximum likelihood estimation with a ridge regression penalty. |