hoa (version 2.1.2)

rsm.fit: Fit a Regression-Scale Model Without Computing the Model Matrix

Description

Fits a rsm model without computing the model matrix of the response vector.

Usage

rsm.fit(X, Y, offset, family, dispersion, score.dispersion, maxit, epsilon, 
        trace, ...)

Arguments

X

the model matrix (design matrix).

Y

the response vector.

dispersion

if NULL, the MLE of the scale parameter is returned, otherwise the scale parameter is fixed to the numerical value passed through the argument. If Huber's least favourable distribution is used and disp

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 val

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.

Value

• an object which is a subset of a rsm object.

Details

The rsm.fit function is called internally by the rsm routine to do the actual model fitting. Although it is not intended to be used directly by the user, it may be useful when the same data frame is used over and over again. It might save computational time, since the model matrix is not created. No formula needs to be specified as an argument. As no weights argument is available, the response Y and the model matrix X must already include the weights if weighting is desired.

See Also

rsm, rsm.surv, rsm.null, rsm.object, rsm.families