gamlss.nn: Support for Function nn()

In gamlss.add: Extra Additive Terms for Generalized Additive Models for Location Scale and Shape

Support for Function nn()

Description

This is support for the smoother function nn() an interface for Brian Reply's nnet() function. It is not intended to be called directly by users.

Usage

gamlss.nn(x, y, w, xeval = NULL, ...)

Arguments

x	the explanatory variables
y	iterative y variable
w	iterative weights
xeval	if xeval=TRUE then predicion is used
...	for extra arguments

Author(s)

Mikis Stasinopoulos [e-mail], Bob Rigby

References

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., and De Bastiani F., (2019) Distributions for Modeling Location, Scale and Shape: Using GAMLSS in R, Chapman and Hall/CRC.

Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, 23(7), 1–46, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v023.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/).

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

fk

gamlss.add documentation built on May 29, 2024, 4:21 a.m.