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Maximum Likelihood Estimation with Stata, 4th Edition by William W Gould; Jeffrey Pitblado; Brian Poi is a book available to read on EtoBox.

What is Maximum Likelihood Estimation with Stata, 4th Edition about?

Maximum Likelihood Estimation with Stata, Fourth Edition is the essential reference and guide for researchers in all disciplines who wish to write maximum likelihood (ML) estimators in Stata. Beyond providing comprehensive coverage of Stata's ml command for writing ML estimators, the book presents an overview of the underpinnings of maximum likelihood and how to think about ML estimation. The book shows you how to take full advantage of the ml command's noteworthy features: - linear constraints - four optimization algorithms (Newton–Raphson, DFP, BFGS, and BHHH) - observed information matrix (OIM) variance estimator - outer product of gradients (OPG) variance estimator - Huber/White/sandwich robust variance estimator - cluster–robust variance estimator - complete and automatic support for survey data analysis - direct support of evaluator functions written in Mata When appropriate options are used, many of these features are provided automatically by ml and require no special programming or intervention by the researcher writing the estimator. The fourth edition has been updated to include new features introduced in recent versions of Stata. Such features include new methods for ha

Author

William W Gould; Jeffrey Pitblado; Brian Poi

Publisher

A Stata Press Publication

Published

2010

Language

EN

ISBN

9781597180788

Subjects

Science, Mathematics, Computer Science