Search results for ""Author Arnold Zellner""
Cambridge University Press Statistics, Econometrics and Forecasting
Based on two lectures presented as part of The Stone Lectures in Economics series, Arnold Zellner describes the structural econometric time series analysis (SEMTSA) approach to statistical and econometric modeling. Developed by Zellner and Franz Palm, the SEMTSA approach produces an understanding of the relationship of univariate and multivariate time series forecasting models and dynamic, time series structural econometric models. As scientists and decision-makers in industry and government world-wide adopt the Bayesian approach to scientific inference, decision-making and forecasting, Zellner offers an in-depth analysis and appreciation of this important paradigm shift. Finally Zellner discusses the alternative approaches to model building and looks at how the use and development of the SEMTSA approach has led to the production of a Marshallian Macroeconomic Model that will prove valuable to many. Written by one of the foremost practitioners of econometrics, this book will have wide academic and professional appeal.
£27.99
John Wiley & Sons Inc An Introduction to Bayesian Inference in Econometrics
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.
£144.95
Edward Elgar Publishing Ltd Bayesian Analysis in Econometrics and Statistics: The Zellner View and Papers
This book presents some of Arnold Zellner's outstanding contributions to the philosophy, theory and application of Bayesian analysis, particularly as it relates to statistics, econometrics and economics. The volume contains both previously published and new material which cite and discuss the work of Bayesians who have made a contribution by helping researchers and analysts in many professions to become more effective in learning from data and making decisions. Bayesian and non-Bayesian approaches are compared in several papers. Other articles include theoretical and applied results on estimation, model comparison, prediction, forecasting, prior densities, model formulation and hypothesis testing. In addition, a new information processing approach is presented that yields Bayes's Theorem as a perfectly efficient information processing rule.This volume will be essential reading for academics and students interested in qualitative methods as well as industrial analysts and government officials.
£161.00
