Maximum likelihood estimation with stata
Maximum likelihood estimation with stata
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使用stata进行最大似然估计
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
Brian P. Poi
中科院分区：
文献类型：
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作者：
W. Gould;J. Pitblado;Brian P. Poi
最大似然估计与统计，第四版是为研究人员在所有学科谁需要计算最大似然估计，是不可用的预包装例程。读者应该熟悉Stata，但除了最后几章，没有特殊的编程技能，这几章详细介绍了如何向Stata添加新的估计命令。这本书首先介绍了最大似然估计理论，特别注意应用工作的实际影响。然后，各章详细描述了四种可能性评估程序中的每一种，并提供了许多例子，如logit和probit回归，Weibull回归，随机效应线性回归和考克斯比例风险模型。后面的章节和附录提供了关于ml命令的更多细节，提供了编写求值器时要遵循的检查表，并展示了如何编写自己的估计命令。
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.