If the grouping factor corresponding to
object
is included in
newdata,
the data frame is partitioned according to the grouping factor levels;
else,
newdata is repeated for all
glm
components.
The predictions
and, optionally, the standard errors for the predictions,
are obtained for each
glm component
of
object,
using the corresponding element of the partitioned
newdata
,
and arranged into a list with as many components
as
object,
or combined into a single vector or data frame
(if
se.fit=TRUE).
an object inheriting from class
glmList,
representing a list of
glm objects
with a common model.
newdata
an optional data frame to be used for obtaining the predictions.
All variables used in the
object model formula
must be present in the data frame.
If missing, the same data frame used
to produce
object is used.
type
an optional character string indicating the type of predicted
values to be obtained for the
glm fits,
with choices
"response"
and
"link".
Partial matching of arguments is used,
so only the first character needs to be provided.
Default is
"response".
subset
an optional character or integer vector naming the
glm components of
object from which the predictions
are to be extracted.
Default is
NULL,
in which case all components are used.
asList
an optional logical value.
If
TRUE,
the returned object is a list with the predictions split by groups;
else the returned value is a vector.
Defaults to
FALSE.
se.fit
an optional logical value indicating whether pointwise
standard errors should be computed along with the predictions.
Default is
FALSE.
VALUE:
a list with components given by the predictions
(and, optionally, the standard errors for the predictions)
from each
glm component
of
object,
a vector with the predictions from all
glm
components of
object,
or a data frame with columns given by the predictions
and their corresponding standard errors.