Gamma MLEParameter Estimator
Estimates the parameters of the Gamma distribution based on a MLE algorithm. See page 285-286 of Law (2007) Simulation Modeling and Analysis. Uses bi-section search seeded by initial estimates based on MOM estimates. Convergence is not guaranteed and will be indicated in the EstimatedParameters success property and the message. Requires that the data be strictly positive and that there are at least two observations. Also, requires that all the supplied data are not equal. The user may vary some of the search control parameters to assist with convergence.
Properties
Indicates if the estimator requires that the range of the data be checked for a shift before the estimation process.
How close we consider a double is to 0.0 to consider it 0.0 Default is 0.001
Desired precision. The default is 0.0001.
The factor used to form initial search interval around initial MOM estimate of the shape. The default is 3.0, as in a 3-sigma range.
Maximum allowed number of iterations. The default is 100.
The type of random variable for which this estimator estimates parameters.
Functions
If the estimation process is not successful, then an empty array is returned.
Estimates the parameters associated with some distribution. The returned EstimationResult needs to be consistent with the intent of the desired distribution. Note the meaning of the fields associated with EstimationResult