Overview of Maximum Likelihood Estimation
In ordinary least squares multiple regression, the objective in fitting a model is to find the values of the unknown parameters that minimize the sum of squared errors of prediction. When the response variable is polytomous or is not observed completely, a more general objective to optimize is needed.
KeywordsMaximum Likelihood Estimate Penalty Function Wald Statistic Bootstrap Distribution Observe Information Matrix
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