# smooth_check

From bamlss v1.1-2
by Nikolaus Umlauf

##### MCMC Based Simple Significance Check for Smooth Terms

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.

- Keywords
- regression

##### 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)
# }
```

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

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