Maximum Likelihood Estimation: Logic And Practice - Couverture souple

Livre 148 sur 194: Quantitative Applications in the Social Sciences

Eliason, Scott R.

 
9780803941076: Maximum Likelihood Estimation: Logic And Practice

Synopsis

In this volume the underlying logic and practice of maximum likelihood (ML) estimation is made clear 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 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 ML solutions; the general form of the covariance matrix for ML estimates; the sampling distribution of ML estimators; the application of ML in the normal distribution as well as in other useful distributions; and some helpful illustrations of likelihoods.

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À propos de l?auteur

RESEARCH AND TEACHING INTERESTS
Quantitative Methodology and Statistics; Sociology of Work, Occupations, and Labor Markets;
Economic Sociology; Stratification; Life Course

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