marg: rsm.null – R documentation

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marg

rsm.null

Fit an Empty Regression-Scale Model

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.