Scott R Eliason

Maximum Likelihood Estimation

Logic and Practice

• Broschiertes Buch

Produktbeschreibung

In this volume the underlying logic and practice of maximum likelihood (ML) estimation is made clear by providing a general modelling framework that utilizes the tools of ML methods. This framework offers readers a flexible modelling 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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Produktdetails

• Verlag: Sage Publications
• Seitenzahl: 96
• Erscheinungstermin: 9. August 1993
• Englisch
• Abmessung: 200mm x 139mm x 6mm
• Gewicht: 118g
• ISBN-13: 9780803941076
• ISBN-10: 0803941072
• Artikelnr.: 22200271

Autorenporträt

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

Inhaltsangabe

Introduction
The Logic of Maximum Likelihood
A General Modeling Framework Using Maximum Likelihood Methods
An Introduction to Basic Estimation Techniques
Further Empirical Examples
Additional Likelihoods
Conclusions