Maximum likelihood estimation with Stata
著者
書誌事項
Maximum likelihood estimation with Stata
Stata Press, 2010
4th ed
- : pbk
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注記
Includes bibliographical references and indexes
内容説明・目次
内容説明
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.
目次
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.
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