coef.bamlss

From bamlss v1.1-2 by Nikolaus Umlauf

Extract BAMLSS Coefficients

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.

Keywords: models, regression

Usage

# 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, ...)

Arguments

object: An object of class "bamlss"
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 TRUE, additionally adds estimated parameters returned from an optimizer function (if available).
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 scale.d argument in bamlss.frame is set to TRUE.
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 FUN and function samples.

Value

Depending on argument list and the number of distributional parameters, either a list or vector/matrix of model coefficients.

Examples

# 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)
# }

Documentation reproduced from package bamlss, version 1.1-2, License: GPL-2 | GPL-3

Community examples

Looks like there are no examples yet.