Read Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96)

Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96)

Scott R. Eliason

4.9/5 (9380 ratings)

Description:"Maximum Likelihood Estimation. . . provides a useful introduction. . . it is clear and easy to follow with applications and graphs. . . . I consider this a very useful book. . . . well-written, with a wealth of explanation. . ."--Dougal Hutchison in Educational ResearchEliason reveals to the reader the underlying logic and practice of maximum likelihood (ML) estimation by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96). To get started finding Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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ISBN: 1506315909

Description: "Maximum Likelihood Estimation. . . provides a useful introduction. . . it is clear and easy to follow with applications and graphs. . . . I consider this a very useful book. . . . well-written, with a wealth of explanation. . ."--Dougal Hutchison in Educational ResearchEliason reveals to the reader the underlying logic and practice of maximum likelihood (ML) estimation by providing a general modeling framework that utilizes the tools of ML methods. This framework offers readers a flexible modeling strategy since it accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models that link a system of endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, Eliason discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96). To get started finding Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96)

Maximum Likelihood Estimation: Logic and Practice (Quantitative Applications in the Social Sciences Book 96)

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