# residuals.bamlss

##### Compute BAMLSS Residuals

Function to compute quantile and response residuals.

- Keywords
- models, regression

##### Usage

```
# S3 method for bamlss
residuals(object, type = c("quantile", "response"),
nsamps = NULL, ...)
```# S3 method for bamlss.residuals
plot(x, which = c("hist-resid", "qq-resid"),
spar = TRUE, ...)

##### Arguments

- object
An object of class

`"bamlss"`

.- type
The type of residuals wanted, possible types are

`"quantile"`

residuals and`"response"`

residuals.- nsamps
If the fitted

`bamlss`

object contains samples of parameters, computing residuals may take quite some time. Therefore, to get a first feeling it can be useful to compute residuals only based on`nsamps`

samples, i.e.,`nsamps`

specifies the number of samples which are extracted on equidistant intervals.- x
Object returned from function

`residuals.bamlss()`

.- which
Should a histogram with kernel density estimates be plotted or a qq-plot?

- spar
Should graphical parameters be set by the plotting function?

- …
For function

`residuals.bamlss()`

arguments passed to possible`$residuals()`

functions that may be part of a`bamlss.family`

. For function`plot.bamlss.residuals()`

arguments passed to function`hist.default`

and`qqnorm.default`

.

##### Details

Response residuals are the raw residuals, i.e., the response data minus the fitted distributional
mean. If the `bamlss.family`

object contains a function `$mu(par, …)`

, then
raw residuals are computed with `y - mu(par)`

where `par`

is the named list of fitted
values of distributional parameters. If `$mu(par, ...)`

is missing, then the fitted values
of the first distributional parameter are used.

Randomized quantile residuals are based on the cumulative distribution function of the
`bamlss.family`

object, i.e., the `$p(y, par, ...)`

function.

##### Value

A vector of residuals.

##### References

Dunn P. K., and Smyth G. K. (1996). Randomized Quantile Residuals.
*Journal of Computational and Graphical Statistics* **5**, 236-244.

##### See Also

##### Examples

```
# NOT RUN {
## Generate data.
d <- GAMart()
## Estimate models.
b1 <- bamlss(num ~ s(x1), data = d)
b2 <- bamlss(num ~ s(x1) + s(x2) + s(x3), data = d)
## Extract quantile residuals.
e1 <- residuals(b1, type = "quantile")
e2 <- residuals(b2, type = "quantile")
## Plots.
plot(e1)
plot(e2)
# }
```

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