`coef.bamlss.Rd`

Methods to extract coefficients of fitted `bamlss`

objects, either coefficients
returned from optimizer functions, or samples from a sampler functions.

Method `confint.bamlss()`

produces credible intervals or parameter samples
using quantiles.

# S3 method for bamlss coef(object, model = NULL, term = NULL, FUN = NULL, parameters = NULL, pterms = TRUE, sterms = TRUE, hyper.parameters = TRUE, list = FALSE, full.names = TRUE, rescale = FALSE, ...) # S3 method for bamlss confint(object, parm, level = 0.95, model = NULL, pterms = TRUE, sterms = FALSE, full.names = FALSE, hyper.parameters = FALSE, ...)

object | An object of class |
---|---|

model | Character or integer. For which model should coefficients be extracted? |

term | Character or integer. For which term should coefficients be extracted? |

FUN | A function that is applied on the parameter samples. |

parameters | If is set to |

pterms | Should coefficients of parametric terms be included? |

sterms | Should coefficients of smooths terms be included? |

hyper.parameters | For smooth terms, should hyper parameters such as smoothing variances be included? |

list | Should the returned object have a list structure for each distribution parameter? |

full.names | Should full names be assigned, indicating whether a term is parametric "p" or smooth "s". |

rescale | Should parameters of the linear parts be rescaled if the |

parm | Character or integer. For which term should coefficients intervals be extracted? |

level | The credible level which defines the lower and upper quantiles that should be computed from the samples. |

… | Arguments to be passed to |

Depending on argument `list`

and the number of distributional parameters, either a
`list`

or vector/matrix of model coefficients.

# NOT RUN { ## Simulate data. d <- GAMart() ## Model formula. f <- list( num ~ s(x1) + s(x2) + s(x3), sigma ~ s(x1) + s(x2) + s(x3) ) ## Estimate model. b <- bamlss(f, data = d) ## Extract coefficients based on MCMC samples. coef(b) ## Now only the mean. coef(b, FUN = mean) ## As list without the full names. coef(b, FUN = mean, list = TRUE, full.names = FALSE) ## Coefficients only for "mu". coef(b, model = "mu") ## And "s(x2)". coef(b, model = "mu", term = "s(x2)") ## With optimizer parameters. coef(b, model = "mu", term = "s(x2)", parameters = TRUE) ## Only parameteric part. coef(b, sterms = FALSE, hyper.parameters = FALSE) ## For sigma. coef(b, model = "sigma", sterms = FALSE, hyper.parameters = FALSE) ## 95 perc. credible interval based on samples. confint(b) # }