Given an appropriate DL model formula and data-frame, prepares the data to be fit by interpreting the formula and extracting available smooth lag terms.
a symbolic description of the model to be fitted.
a model-frame containing the data for each term in the model. Should already be appropriately subset, etc.
a function for creating names of dummy variables that act as placeholders for penalized spline terms in lme4's setup. There should not be a need to alter this in normal use cases
Users should not typically have to interact with
directly, but it may be useful for extensions.
stats::model.matrix mechanisms to build
and parse the random effects (or penalized) components of spline-lag terms
in the model. The object returned is later passed to other dlmBE
functions in order to fit the specified model.
an S3 object of class
"parsed.dlm" with list elements:
the formula passed to
a reconstructed formula that is then passed
to the lme4
data.frame returned by call to
stats::model.frame; a copy of the fixed
effects data needed to fit the model
a matrix of the random or penalized lag basis vectors,
where each vector is a row. Stored as an object that inherits from
a list of all the unique bases represented in the
formula. This may be <= the number of separate
spline-lag terms. All elements should inherit from
an integer vector returned by
parse.names where each unique integer corresponds to a
separate spline-lag term. For lag term
lag.group == i
indexes the rows of
Bt that correspond to the set of random or
penalized basis vectors for that term
for "basis index." Each set of lag terms indexed in
lag.group has a matching basis decomposition in
bi keeps track of that matching
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