Introduction to Bayesian Econometrics
- Textbook
Description
This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior distributions are considered, with special emphasis on subject-matter considerations and exchange ability. The regression model is examined to show how analytical methods may fail in the…
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Key features
- New chapter on semiparametric regression, new sections on ordinal probit, item response, facto analysis, ARCH-GARCH and stochastic volatility models
- New edition emphasizes the R programming language, the most widely used environment for Bayesian statistics
- Clear, concise explanation of how Bayesian approach arises from basic principles of probability theory emphasizing Markov chain Monte Carlo methods
About the book
- DOI https://doi.org/10.1017/CBO9781139058414
- Subjects Computational Science,Econometrics and Mathematical Methods,Economics,Mathematics
- Format: Hardback
- Publication date: 12 November 2012
- ISBN: 9781107015319
- Dimensions (mm): 253 x 177 mm
- Weight: 0.64kg
- Contains: 29 b/w illus. 19 tables
- Page extent: 270 pages
- Availability: Available
- Format: Paperback
- Publication date: 21 August 2014
- ISBN: 9781107436770
- Dimensions (mm): 254 x 178 mm
- Weight: 0.47kg
- Contains: 29 b/w illus. 19 tables
- Page extent: 270 pages
- Availability: Available
- Format: Digital
- Publication date: 05 December 2012
- ISBN: 9781139058414
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