For each model term in the "smooth.construct"
object of the x
list (as returned
from bamlss.frame
), this function adds a named list called "state"
with the
following entries:
"parameters"
: A numeric vector. Regression coefficients are named with "b"
,
smooth variances are named with "tau2"
.
"fitted.values"
: Given the "parameters"
, the actual fitted values of
the model term.
"edf"
: Given the smoothing variances, the actual equivalent degrees of freedom
(edf) of the model term.
"do.optim"
: Should an optimizer function try to find optimum smoothing variances?
The state will be changed in each iteration and can be passed outside an updating function.
Additionally, if missing in the xt
argument of a model term (see, e.g., function
s
for xt
) the function adds the corresponding log-prior and its first
and second order derivatives w.r.t. regression coefficients in functions grad()
and
hess()
.
Also, objects named "lower"
and "upper"
are added to each model term. These
indicate the lower and upper boundaries of the parameter space.