est.max.like
Maximum likelihood estimation
Description
Maximum likelihood estimation.
Usage
est.max.like(model, max.iter=20, ftol=1e-5, algorithm='nlmin')
Required Arguments
- model
-
An object of class TSestModel, or a previously returned result from max.like.
Optional Arguments
- max.iter
-
The maximum number of iterations.
- ftol
-
The function tolerance for indicating convergence.
- algorithm
-
The algorithm ('nlmin' or 'dfpMin') to use for maximization.
Value
The value returned is an object of class TSestModel with additional
elements $converged, which is T or F indicating convergence,
and $dfpMin.results or $nlmin.results.
If this function calls dfp the Hessian,etc are return as $dfpMin.results.
If this function is called again and those results are
available then they are used.
This could cause problems if $model is modified. If that is
done then $dfpMin.results should be set to NULL.
See Also
Examples
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