gamlss.nn {gamlss.add}

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, 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