logpost.Gauss(object, theta = <<see below>>, prior = <<see below>>)
"missmodel" whose
paramIter component is of
class
"Gauss". I.e., an object resulting from the use of the
mdGauss,
daGauss, or
emGauss functions. Alternatively, a class
"preGauss" object.
paramIter component
of the input
missmodel object. If a class
"preGauss" object is
input, the model parameters must be specified exactly as in a class
"Gauss" object (see
).
"Gauss" object with multiple rows; then calculations
are performed for each row, and a vector is returned.
"priorGauss".
"ml" (maximum likelihood),
"noninformative", and
"ridge" (for the default ridge prior).
String matching is used, so the characters
"m",
"n", or
"r" are
sufficient.
"priorGauss" object is created by routine
priorGauss.
"missmodel" object is input, any value specified in a previous call
has priority over the default value (but not over any currently
specified value).
theta.
This is the log-likelihood or log-posterior density that ignores the missing-data mechanism.
fit <- emGauss(cholesterol) logpost.Gauss(fit)