rsm.null: Fit an Empty Regression-Scale Model

In hoa: Higher Order Likelihood Inference

Description

Fits a rsm model with empty model matrix.

Usage

rsm.null(X = NULL, Y, offset, family, dispersion, score.dispersion, maxit, 
         epsilon, trace, ...)

Arguments

X	defaults to NULL.
Y	the response vector.
dispersion	either NULL or TRUE. If NULL, the MLE of the scale parameter is returned. If Huber's least favourable distribution is used and dispersion is TRUE, the MAD is computed and the scale parameter fixed to this value in subsequent calculations.
score.dispersion	must default to NULL.
offset	optional offset added to the linear predictor.
family	a family.rsm object, i.e. a list of functions and expressions characterizing the error distribution. Families supported are gaussian, student (Student's t), extreme (Gumbel or extreme value), logistic, logWeibull, logExponential, logRayleigh and Huber (Huber's least favourable). Users can construct their own families, as long as they have components compatible with those given in rsm.distributions. The demonstration file ‘margdemo.R’ that ships with the package shows how to create a new generator function.
maxit	maximum number of iterations allowed.
epsilon	convergence threshold.
trace	if TRUE, iterations details are printed during execution.
...	not used, but do absorb any redundant argument.

Details

The rsm.null function is called internally by the rsm routine to do the actual model fitting in case of an empty model. It is not intended to be used directly by the user. As no weights argument is available, the response Y and the model matrix X must already include the weights if weighting is desired.

Value

an object which is a subset of a rsm object.

See Also

rsm, rsm.surv, rsm.fit, rsm.object, rsm.families

hoa documentation built on May 2, 2019, 8:56 a.m.