bamlss: smooth_check – R documentation

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smooth_check

MCMC Based Simple Significance Check for Smooth Terms

Description

For each smooth term estimated with MCMC, the function computes 95 intervals and simply computes the fraction of the cases where the interval does not contain zero.

Usage

smooth_check(object, newdata = NULL, model = NULL, term = NULL, ...)

Arguments

`object`	A fitted model object which contains MCMC samples.
`newdata`	Optionally, use new data for computing the check.
`model`	Character, for which model should the check be computed?
`term`	Character, for which term should the check be computed?
`...`	Arguments passed to `predict.bamlss`.

Examples

## Not run: ## Simulate some data.
d <- GAMart()

## Model formula.
f <- list(
  num ~ s(x1) + s(x2) + s(x3),
  sigma ~ s(x1) + s(x2) + s(x3)
)

## Estimate model with MCMC.
b <- bamlss(f, data = d)

## Run the check, note that all variables
## for sigma should have no effect.
smooth_check(b)

## End(Not run)

bamlss

Bayesian Additive Models for Location, Scale, and Shape (and Beyond)

v1.1-3

GPL-2 | GPL-3

Authors

Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>), Nadja Klein [aut] (<https://orcid.org/0000-0002-5072-5347>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Meike Koehler [ctb], Thorsten Simon [aut] (<https://orcid.org/0000-0002-3778-7738>), Stanislaus Stadlmann [ctb]

Initial release

2021-01-25