rsm.null {marg} | R Documentation |
Fits a rsm
model with empty model matrix.
rsm.null(X = NULL, Y, offset, family, dispersion, maxit, epsilon, trace, ...)
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.
|
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. |
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.
an object which is a subset of a rsm
object.
rsm
, rsm.surv
, rsm.fit
,
rsm.object
, rsm.families