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
the fitted values
the residuals
the variance of the fitted values
the final lambda, the smoothing parameter
with value NULL
the explanatory design matrix
the response variable
iterative weights
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