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gamlss (version 5.1-4)

additive.fit: Implementing Backfitting in GAMLSS

Description

This function is not to be used on its own. It is used for backfitting in the GAMLSS fitting algorithms and it is based on the equivalent function written by Trevor Hastie in the gam() S-plus implementation, (Chambers and Hastie, 1991).

Usage

additive.fit(x, y, w, s, who, smooth.frame, maxit = 30, tol = 0.001, 
             trace = FALSE, se = TRUE, ...)

Arguments

x

the linear part of the explanatory variables

y

the response variable

w

the weights

s

the matrix containing the smoothers

who

the current smoothers

smooth.frame

the data frame used for the smoothers

maxit

maximum number of iterations in the backfitting

tol

the tolerance level for the backfitting

trace

whether to trace the backfitting algorithm

se

whether standard errors are required

for extra arguments

Value

Returns a list with the linear fit plus the smothers

Details

This function should not be used on its own

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.

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, http://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 http://www.gamlss.org/).

See Also

gamlss