Items related to Bayesian Analysis of Reduced Form Systems (Classic...
Synopsis
Excerpt from Bayesian Analysis of Reduced Form Systems
They, in effect, do prior-posterior analysis of the data generating process defined in (1b) and derive the unconditional distribution of the zij) under the assumption that (g, 2) has a particular diffuse (and degenerate) prior density.
About the Publisher
Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com
This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
"synopsis" may belong to another edition of this title.
- PublisherForgotten Books
- Publication date2019
- ISBN 10 1334538840
- ISBN 13 9781334538841
- BindingPaperback
- LanguageEnglish
- Number of pages47
Search results for Bayesian Analysis of Reduced Form Systems (Classic...
Seller Image
Bayesian Analysis of Reduced Form Systems (Classic Reprint)
Print on DemandSeller: Forgotten Books, London, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. Print on Demand. In an era marked by evolving statistical methodologies, this book delves into the intricacies of Bayesian analysis applied to econometric systems. The author meticulously examines the challenges of uncertainty surrounding parameters in economic models, offering a comprehensive framework for understanding and addressing these complexities. The core of the book lies in the exploration of "reduced form systems" ΓΆβ β a specific type of econometric model. Through rigorous mathematical derivations and insightful explanations, the author guides readers through the process of applying Bayesian principles to these systems. This involves identifying natural conjugate families of prior densities, conducting prior-posterior and preposterior analysis, and deriving sampling distributions that are crucial for statistical inference. A significant contribution of this work is the presentation of a novel procedure for obtaining non-degenerate joint posterior and preposterior distributions, even in situations where the number of sample observations falls short of the number of parameters. This breakthrough empowers researchers to draw meaningful conclusions from limited data, enhancing the applicability of Bayesian methods in real-world econometric analysis. By bridging the gap between theoretical concepts and practical applications, this book provides invaluable insights into the potential of Bayesian analysis for understanding complex economic phenomena. The author's meticulous approach and clear explanations make this work an essential resource for researchers and students seeking to navigate the intricacies of econometric modeling in the face of uncertainty. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781334538841_0
Quantity: Over 20 available
Stock Image
Bayesian Analysis of Reduced Form Systems Classic Reprint
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 4 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781334538841
Quantity: 15 available
Stock Image
Bayesian Analysis of Reduced Form Systems Classic Reprint
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LW-9781334538841
Quantity: 15 available