print.moc {moc} | R Documentation |
print.moc
prints information contained in a fitted moc
object. The attributes
parameters of the functions
gmu
, gshape
, gextra
and gmixture
will be
used to label the output.
fitted.moc
computes the expected values for each observation
of a moc
object using its expected
function.
obsfit.moc
computes and prints the mean posterior
probabilities and the posterior means of a user specified function of
the expected and observed values, separated with respect
to the specified variable.
## S3 method for class 'moc': print(x, digits = 5, ...) ## S3 method for class 'moc': fitted(object, ...) obsfit.moc(object, along = list(cons = rep(1, object$nsubject)), FUN = function(x) x)
x, object |
Objects of class moc . |
digits |
Number of digits to be printed. |
along |
Splitting variable. |
FUN |
User defined function to apply to observed and expected values. |
... |
Unused. |
obsfit.moc
will first compute the posterior probabilities
for all subjects in each mixture using post.moc
and
then the weighted posterior mean probabilities
Sum_i (wt[i] * post[i,k]) / Sum_i wt[i]
The weighted posterior means of a function g() of the data (which are the empirical estimators of the conditional expectation given mixture group) are computed as
Sum_i (wt[i] * post[i,k] * g(y[i])) / Sum_i (wt[i] * post[i,k])
where both sums are taken over index of valid data y[i].
All these methods return their results invisibly.
Bernard Boulerice <Bernard.Boulerice@sympatico.ca>
moc
, residuals.moc
, post.moc
,
plot.moc
, AIC.moc