In this new and expanding area, Tony Lancaster's text is the first comprehensive introduction to the Bayesian way of doing applied economics.
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Tony Lancaster is Herbert H. Goldberger Professor of Economics and Professor of Community Health at Brown University. He is the author of The Econometric Analysis of Transition Data (1990), an Econometric Society Monograph.
About two hundred and forty years ago, an English clergyman named Thomas Bayes developed a method to calculate the chances of uncertain events in the light of accumulating evidence. Though his method has extensive applications to the work of economists, it is only recent advances in computing that have made it possible to exploit its full power.
In this new and expanding area, Tony Lancaster’s text provides a comprehensive introduction to the Bayesian way of doing applied economics. Using clear explanations and practical illustrations and problems, the text presents innovative, computer-intensive ways for applied economists to use the Bayesian method. In addition, each chapter includes numerical and graphical examples and demonstrates their solutions using the S programming language and Bugs software.
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Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
Paperback. Condición: Good. * Provides a comprehensive introduction to the Bayesian way of doing applied economics * Emphasizes computation and the study of probability distributions by computer sampling * Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software. Nº de ref. del artículo: CIN1405117206G
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Librería: World of Books Inc, Montgomery, IL, Estados Unidos de America
Paperback. Condición: Good. * Provides a comprehensive introduction to the Bayesian way of doing applied economics * Emphasizes computation and the study of probability distributions by computer sampling * Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software. Nº de ref. del artículo: CIN1405117206G
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