R: MCMC Based Simple Significance Check for Smooth Terms

smooth_check {bamlss} | R Documentation

## 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)

[Package bamlss version 1.1-7 Index]