mmlcrcomponentinit {mmlcr} | R Documentation |
Used internally by mmlcr
to initialize an mmlcr
component. The function is generic.
mmlcrcomponentinit(object, n.groups, prob, data, grouping)
object |
see details below |
n.groups |
the number of classes. Provided by mmlcr .
|
prob |
a data.frame of (initial) posterior probabilities of class
membership. Provided by mmlcr .
|
data |
a data.frame. Provided by mmlcr .
|
grouping |
the variable of data indicating subject id. Provided by mmlcr .
|
The object argument is a list, originally provided to the mmlcr
function as a
component of a list in the components argument. At a minimum, that list consists
of a formula of the form resp ~ covars
, where resp is the response variable for
that component and covars are any additional covariates (resp ~ 1
is commonly
used), and a class. For longitudinal responses, the covariates should include
the chronological variable, e.g., resp ~ poly(age, 2)
. Implemented classes include
cnormlong
, cnormonce
, multinomlong
, multinomonce
, nblong
, nbonce
,
normlong
, normonce
, poislong
, and poisonce
. The *long
classes are for longitudinal
responses, while the *once
classes are for one-time responses. So that a rectangular
data structure can be used for the data argument in mmlcr
, the *once
classes use
just the first occurence of a response for each subject.
The cnorm
* classes are for censored normal distributions. They take a min
and max
argument for the minimum and maximum possible observed value. The multinom
* classes
are for multinomial, or categorical responses. The response variable should be
a factor. The nb
* classes are for
negative binomial models (the usual overdispersed Poisson model). The norm
* classes
are for normal models, and the pois
* classes are for Poisson models. For the cnorm
*
and norm
* classes the minimum and maximum variances are constrained to be within a
factor of 100 of each other. For the pois
* classes an overdispersion estimate is
calculated but not used.
an mmlcr
component object.