Maximum Likelihood Estimation with Stata, Fourth Edition

William Gould (Autor)

Buch | Softcover

352 Seiten

2010 | 4th edition
Stata Press (Verlag)
978-1-59718-078-8 (ISBN)

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Maximum Likelihood Estimation with Stata, Fifth Edition

Jeffrey Pitblado, Brian Poi, William Gould

2023

Buch | Softcover

CHF 118, ⁴⁵

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Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.

William Gould is president of StataCorp and heads the technical development of Stata. He is also the architect of Mata, Stata’s matrix programming language. Jeff Pitblado is associate director of statistical software at StataCorp. He has played a leading role in the development of ml through adding the ability of ml to work with survey data and writing the current implementation of ml in Mata. Brian Poi is senior economist at StataCorp. On the software development side, he has written a variety of econometric estimators in Stata.

Theory and Practice. Introduction to ml. Overview of ml. Method lf. Methods lf0, lf1, and lf2. Methods d0, d1, and d2. Debugging Likelihood Evaluators. Setting Initial Values. Interactive Maximization. Final Results. Mata-Based Likelihood Evaluators. Writing Do-Files to Maximize Likelihoods. Writing Ado-Files to Maximize Likelihoods. Writing Ado-Files for Survey Data Analysis. Appendices. Indices.

Erscheint lt. Verlag	29.11.2010
Verlagsort	College Station
Sprache	englisch
Maße	152 x 229 mm
Gewicht	750 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
ISBN-10	1-59718-078-5 / 1597180785
ISBN-13	978-1-59718-078-8 / 9781597180788
Zustand	Neuware