R: Support for Functions random() and re()

gamlss.random {gamlss} | R Documentation

## Support for Functions random() and re()

### Description

This is support for the functions `random()` and `re()` respectively. It is not intended to be called directly by users. .

### Usage

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

### Arguments

`x` | the explanatory design matrix
`y` | the response variable
`w` | iterative weights
`xeval` | it used internaly for prediction
`...` | for extra arguments

### Value

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

### Author(s)

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

### References

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/).

### See Also

`gamlss`, `random`

[Package gamlss version 5.3-2 Index]