An Introduction to Bayesian Inference in Econometrics - Info and Reading Options
By Arnold Zellner
"An Introduction to Bayesian Inference in Econometrics" was published by John Wiley & Sons, Inc. in 1996 - New York, the book is classified in Mathematics genre, it has 431 pages and the language of the book is English.
“An Introduction to Bayesian Inference in Econometrics” Metadata:
- Title: ➤ An Introduction to Bayesian Inference in Econometrics
- Author: Arnold Zellner
- Language: English
- Number of Pages: 431
- Is Family Friendly: Yes - No Mature Content
- Publisher: John Wiley & Sons, Inc.
- Publish Date: 1996
- Publish Location: New York
- Genres: Mathematics
“An Introduction to Bayesian Inference in Econometrics” Subjects and Themes:
- Subjects: ➤ Bayesian statistical decision theory - Econometrics - Econometria - Decisiones - Teoría - Estadística bayesiana - Économétrie - Statistique bayésienne - Econometrie - Methode van Bayes - BAYES
Edition Specifications:
- Pagination: xv,431p. :
Edition Identifiers:
- Google Books ID: 9tSrQgAACAAJ
- The Open Library ID: OL22279211M - OL3350935W
- Online Computer Library Center (OCLC) ID: 214891 - 35910733
- Library of Congress Control Number (LCCN): 70156329
- ISBN-13: 9780471169376 - 9780471981657
- ISBN-10: 0471169374
- All ISBNs: 0471169374 - 9780471169376 - 9780471981657
AI-generated Review of “An Introduction to Bayesian Inference in Econometrics”:
Snippets and Summary:
This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics.
What Moore has said about discussing work in art is undoubtedly applicable to discussions of methodology in economics.
"An Introduction to Bayesian Inference in Econometrics" Description:
Google Books:
This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics. This historical volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The coverage ranges from the fundamental concepts and operations of Bayesian inference to analysis of applications in specific econometric problems and the testing of hypotheses and models.
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