expInfo.nlreg: Expected Information Matrix for 'nlreg' Objects

In hoa: Higher Order Likelihood Inference

Description

Returns the expected information matrix for a fitted nlreg model.

Usage

## S3 method for class 'nlreg'
expInfo(object, par, mu, v, m1 = NULL, v1 = NULL, ...)

Arguments

object	a fitted nlreg object such as returned by a call to nlreg.
par	a vector of parameter values where each element is named after the parameter it represents. If missing, the values in the ws$allPar component of object are used.
mu	numerical vector containing the mean function evaluated at each data point. If missing, the fitted values saved in object are used.
v	numerical vector containing the variance function evaluated at each data point. If missing, the values of the weights component of object are used.
m1	a matrix whose rows represent the gradients of the mean function evaluated at each data point. If NULL, the gradient attribute of the object returned by a call to Dmean is used.
v1	a matrix whose rows represent the gradient of the variance function evaluated at each data point. If NULL, the gradient attribute of the object returned by a call to Dvar is used.
...	absorbs any additional argument.

Details

This function is a method for the generic function expInfo for objects inheriting from class nlreg.

Value

the expected information matrix of the fitted nonlinear model passed through the object argument.

Note

This function is mostly intended for internal use. It is called by functions such as nlreg.diag, summary.nlreg and profile.nlreg. To extract the expected information matrix from a fitted nlreg object, the generic method expInfo should be used.

See Also

expInfo, nlreg.object, obsInfo

hoa documentation built on May 2, 2019, 8:56 a.m.