2003 TutorialOnMLE

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Subject Headings: Maximum Likelihood Estimator, Least Squares Estimator.

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Abstract

In this paper, I provide a tutorial exposition on maximum likelihood estimation (MLE). The intended audience of this tutorial are researchers who practice mathematical modeling of cognition but are unfamiliar with the estimation method. Unlike least-squares estimation which is primarily a descriptive tool, MLE is a preferred method of parameter estimation in statistics and is an indispensable tool for many statistical modeling techniques, in particular in non-linear modeling with non-normal data. The purpose of this paper is to provide a good conceptual explanation of the method with illustrative examples so the reader can have a grasp of some of the basic principles.


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2003 TutorialOnMLEIn Jae MyungTutorial on Maximum Likelihood EstimationJournal of Mathematical Psychologyhttp://faculty.psy.ohio-state.edu/myung/personal/mle.pdf10.1016/S0022-2496(02)00028-7
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