logbin.smooth
,
logbin.smooth.allref
takes the formula and data
for a log-link binomial GLM with smooth terms and produces a
list of all parameterizations needed for the CEM algorithm
associated with the semi-parametric part of the model.logbin.smooth.allref(object, data = environment(object), mono,
logbin.smooth.spec, num.knots)
terms
object for the "fake.formula
"
associated with an logbin.smooth
model
(see
get_all_vars
for
the fake.formula
.fake.formula
should be restricted to have a
monotonically non-decreasing relationship with the
outcome. May be specified as names or indices of the
terms.interpret.logbin.smooth
.NA
for Iso
terms).terms
component of object
.data
argument.terms
are restricted to be
monotonically non-decreasing.logbin.smooth
use an extended CEM algorithm
by partioning the parameter space associated with the smooth terms into a
collection of restricted parameter spaces, each corresponding to a
restricted fully parametric model that can be fit using logbin
.
This is a workhorse function that creates the list of possible parameterizations of
each smooth term.
Isotonic terms and monotonic B-spline terms have only one parameterization: where
the maximum fitted value occurs at the maximum of the covariate range.
Unrestricted B-spline terms have k + 3
parameterizations each
(where k
is the number of internal knots), corresponding to the possible
locations of the maximum of the smooth curve along the range of the covariate.
logbin.smooth
considers all possible combinations of the number of
knots for each smooth term, and all possible combinations of the associated
parameterizations, and logbin.smooth.design
creates the appropriate
formula and design matrix to be used in the call to logbin
.logbin.smooth