gamlss (version 5.2-0)

gamlss.fp: Support for Function fp()

Description

Those are support for the functions fp() and pp. It is not intended to be called directly by users.

Usage

gamlss.fp(x, y, w, npoly = 2, xeval = NULL)
gamlss.pp(x, y, w)

Arguments

x

the x for function gamlss.fp is referred to the design matric of the specific parameter model (not to be used by the user)

y

the y for function gamlss.fp is referred to the working variable of the specific parameter model (not to be used by the user)

w

the w for function gamlss.fp is referred to the iterative weight variable of the specific parameter model (not to be used by the user)

npoly

a positive indicating how many fractional polynomials should be considered in the fit. Can take the values 1, 2 or 3 with 2 as default

xeval

used in prediction

Value

Returns a list with

fitted.values

fitted

residuals

residuals

var

nl.df

the trace of the smoothing matrix

lambda

the value of the smoothing parameter

coefSmo

the coefficients from the smoothing fit

varcoeff

the variance of the coefficients

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. 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, fp