The `"respModule"`

class is the virtual base class of
response modules for `glpModel`

model objects.
Classes that inherit from `"respModule"`

include
`glmRespMod`

, for
generalized linear models, `nlsRespMod`

, for
nonlinear models and `nglmRespMod`

for generalized
nonlinear models.

Objects from these classes are usually created with
`mkRespMod`

as part of an `glpModel`

object returned by model-fitting functions such as the hidden function
`glm4`

.

`mu`

:Fitted mean response.

`offset`

:offset in the linear predictor – always present even if it is a vector of zeros. In an

`nlsRespMod`

object the length of the offset can be a multiple of the length of the response.`sqrtXwt`

:the matrix of weights for the model matrices, derived from the

`sqrtrwt`

slot.`sqrtrwt`

:Numeric vector of the square roots of the weights for the residuals. For

`respModule`

and`nlsRespMod`

objects these are constant. For`glmRespMod`

and`nglmRespMod`

objects these are updated at each iteration of the iteratively reweighted least squares algorithm.`weights`

:Prior weights – always present even when it is a vector of ones.

`y`

:Numeric response vector.

`family`

:a glm family, see

`family`

for details -`glmRespMod`

objects only.`eta`

:numeric vector, the linear predictor that is transformed to the conditional mean via the link function -

`glmRespMod`

objects only.`n`

: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) -

`glmRespMod`

objects only.`nlenv`

:an environment in which to evaluate the nonlinear model function -

`nlsRespMod`

objects only.`nlmod`

:an unevaluated call to the nonlinear model function -

`nlsRespMod`

objects only.`pnames`

:a character vector of parameter names -

`nlsRespMod`

objects only.

- fitted
`signature(object = "respModule")`

: fitted values; there may be several types, corresponding to the residuals, see there (below).- residuals
`signature(object = "respModule")`

: residuals, depending on the type of the model, there are several types of residuals and correspondingly residuals, see`residuals.glm`

from 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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