Function to compute/extract a function that returns the information
matrix for an object of class
an object of class
currently not used
The computed/extracted function has arguments
the regression coefficients at which the information matrix is evaluated. If missing then the maximum likelihood estimates are used
the dispersion parameter at which the information matrix is evaluated. If missing then the maximum likelihood estimate is used
should the function return th 'expected' or 'observed' information? Default is
TRUE, then the QR decomposition of
is returned, where
is a diagonal matrix with the working weights (
is the model matrix.
TRUE, then the Cholesky decomposition of the information matrix at the coefficients is returned
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