An Introduction To Bayesian Inference In Econometrics
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An Introduction To Bayesian Inference In Econometrics
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Author : Arnold Zellner
language : en
Publisher:
Release Date : 1971
An Introduction To Bayesian Inference In Econometrics written by Arnold Zellner and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with categories.
Introduction To Bayesian Econometrics
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Author : Edward Greenberg
language : en
Publisher: Cambridge University Press
Release Date : 2013
Introduction To Bayesian Econometrics written by Edward Greenberg and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
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 derivation of marginal posterior distributions. The remainder of the book is concerned with applications of the theory to important models that are used in economics, political science, biostatistics and other applied fields. New to the second edition is a chapter on semiparametric regression and new sections on the ordinal probit, item response, factor analysis, ARCH-GARCH and stochastic volatility models. The new edition also emphasizes the R programming language.
Introduction To Modern Bayesian Econometrics
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Author : Tony Lancaster
language : en
Publisher: Wiley-Blackwell
Release Date : 2004-06-18
Introduction To Modern Bayesian Econometrics written by Tony Lancaster and has been published by Wiley-Blackwell this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-06-18 with Business & Economics categories.
In this new and expanding area, Tony Lancaster’s text is the first comprehensive introduction to the Bayesian way of doing applied economics. Uses clear explanations and practical illustrations and problems to present innovative, computer-intensive ways for applied economists to use the Bayesian method; Emphasizes computation and the study of probability distributions by computer sampling; Covers all the standard econometric models, including linear and non-linear regression using cross-sectional, time series, and panel data; Details causal inference and inference about structural econometric models; Includes numerical and graphical examples in each chapter, demonstrating their solutions using the S programming language and Bugs software Supported by online supplements, including Data Sets and Solutions to Problems, at www.blackwellpublishing.com/lancaster
Bayesian Inference In Dynamic Econometric Models
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Author : Luc Bauwens
language : en
Publisher: Oxford University Press
Release Date : 1999
Bayesian Inference In Dynamic Econometric Models written by Luc Bauwens and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Business & Economics categories.
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques basedon simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditionalheteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
The Oxford Handbook Of Bayesian Econometrics
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Author : Herman van Dijk
language : en
Publisher: Oxford University Press
Release Date : 2011-09-29
The Oxford Handbook Of Bayesian Econometrics written by Herman van Dijk and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-29 with Business & Economics categories.
A broad coverage of the application of Bayesian econometrics in the major fields of economics and related disciplines, including macroeconomics, microeconomics, finance, and marketing.
Introduction To Bayesian Statistics
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Author : William M. Bolstad
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-02
Introduction To Bayesian Statistics written by William M. Bolstad and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-02 with Mathematics categories.
"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.
An Introduction To Bayesian Inference Methods And Computation
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Author : Nick Heard
language : en
Publisher: Springer Nature
Release Date : 2021-10-17
An Introduction To Bayesian Inference Methods And Computation written by Nick Heard and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-17 with Mathematics categories.
These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy and principles of Bayesian inference, including the reasoning behind the prior/likelihood model construction synonymous with Bayesian methods, through to advanced topics such as nonparametrics, Gaussian processes and latent factor models. These advanced modelling techniques can easily be applied using computer code samples written in Python and Stan which are integrated into the main text. Importantly, the reader will learn methods for assessing model fit, and to choose between rival modelling approaches.
Bayesian Econometrics
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Author : Siddhartha Chib
language : en
Publisher: Emerald Group Publishing
Release Date : 2008-12-18
Bayesian Econometrics written by Siddhartha Chib and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-18 with Business & Economics categories.
Illustrates the scope and diversity of modern applications, reviews advances, and highlights many desirable aspects of inference and computations. This work presents an historical overview that describes key contributions to development and makes predictions for future directions.
An Introduction To Bayesian Inference In Econometrics
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Author : Arnold Zellner
language : en
Publisher: Wiley-Interscience
Release Date : 1996-08-17
An Introduction To Bayesian Inference In Econometrics written by Arnold Zellner and has been published by Wiley-Interscience this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-17 with Mathematics categories.
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.
Bayesian Analysis In Statistics And Econometrics
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Author : Donald A. Berry
language : en
Publisher: John Wiley & Sons
Release Date : 1996
Bayesian Analysis In Statistics And Econometrics written by Donald A. Berry and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.
This book is a definitive work that captures the current state of knowledge of Bayesian Analysis in Statistics and Econometrics and attempts to move it forward. It covers such topics as foundations, forecasting inferential matters, regression, computation and applications.