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.

1 2 3 4 5 6 7 8 9 10 11 | ```
## S3 method for class '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 class '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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 | ```
## 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)
## End(Not run)
``` |

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