Maximum Likelihood Techniques: An Overview
In this chapter, we describe the general maximum likelihood (ML) procedure, including a discussion of likelihood functions and how they are maximized. We also distinguish between two alternative ML methods, called the unconditional and the conditional approaches, and we give guidelines regarding how the applied user can choose between these methods. Finally, we provide a brief overview of how to make statistical inferences using ML estimates.
KeywordsLogistic Model Likelihood Function Statistical Inference Nuisance Parameter Discriminant Function Analysis
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