"respModule" and derived classes
"respModule" class is the virtual base class of
response modules for
glpModel model objects.
Classes that inherit from
generalized linear models,
nonlinear models and
nglmRespMod for generalized
Objects from the Class
Objects from these classes are usually created with
mkRespMod as part of an
object returned by model-fitting functions such as the hidden function
Fitted mean response.
offset in the linear predictor – always present even if it is a vector of zeros. In an
nlsRespModobject the length of the offset can be a multiple of the length of the response.
the matrix of weights for the model matrices, derived from the
Numeric vector of the square roots of the weights for the residuals. For
nlsRespModobjects these are constant. For
nglmRespModobjects these are updated at each iteration of the iteratively reweighted least squares algorithm.
Prior weights – always present even when it is a vector of ones.
Numeric response vector.
a glm family, see
familyfor details -
numeric vector, the linear predictor that is transformed to the conditional mean via the link function -
a numeric vector used for calculation of the aic family function (it is really only used with the binomial family but we need to include it everywhere) -
an environment in which to evaluate the nonlinear model function -
an unevaluated call to the nonlinear model function -
a character vector of parameter names -
signature(object = "respModule"): fitted values; there may be several types, corresponding to the residuals, see there (below).
signature(object = "respModule"): residuals, depending on the type of the model, there are several types of residuals and correspondingly residuals, see
residuals.glmfrom the stats package. Because many of these types of residuals are identical except for objects that inherit from "glmRespMod", a separate method is defined for this subclass.
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