This is support for the functions `random()`

and `re()`

respectively.
It is not intended to be called directly by users.
.

```
gamlss.random(x, y, w, xeval = NULL, ...)
gamlss.re(x, y, w, xeval = NULL, ...)
```

Returns a list with

- y
the fitted values

- residuals
the residuals

- var
the variance of the fitted values

- lambda
the final lambda, the smoothing parameter

- coefSmo
with value NULL

- x
the explanatory design matrix

- y
the response variable

- w
iterative weights

- xeval
it used internaly for prediction

- ...
for extra arguments

Mikis Stasinopoulos, based on Trevor Hastie function `gam.random`

Chambers, J. M. and Hastie, T. J. (1991). *Statistical Models in S*, Chapman and Hall, London.

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion),
*Appl. Statist.*, **54**, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019)
*Distributions for modeling location, scale, and shape: Using GAMLSS in R*, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R.
*Journal of Statistical Software*, Vol. **23**, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017)
*Flexible Regression and Smoothing: Using GAMLSS in R*, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

`gamlss`

, `random`