Description
Bayesian Statistics and Marketing describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained include household and consumer panel data on product purchases and survey data, demand models based on micro-economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods.
Written by the leading experts in the field, this unique book:
- Presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models.
- Provides a self-contained introduction to Bayesian methods.
- Includes case studies drawn from the authors' recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems.
- Is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition the book's website hosts datasets and R code for the case studies.
About the Author
Peter E. Rossi is James Collins Professor of Marketing, Statistics and Economics at UCLA Anderson School of Management. Greg M. Allenby is the author of Bayesian Statistics and Marketing, published by Wiley.
Reviews
"... an asset for business schools and marketing researchers." (Technometrics, May 2007)
"'Bayesian Statistics and Marketing' comes from three pioneers in the field of market research and fills a hole in the existing literature on the topic." (Journal of the American Statistical Association, December 2006)
"... extremely useful to both researchers and practitioners who are interested in understanding the power of these methods for solving important marketing problems." (Journal of Marketing, October 2006)
"This book deserves to be widely adopted by business schools, and widely read by more numerate marketing practitioners." (Short Book Reviews, April 2006)
"... valuable to marketing researchers and others working on related applications, especially if they use advanced logistic and probit models." (JRSSA, Vol. 169, No. 4, October 2006)
"... an excellent book for researchers in applied Bayesian statistics." (Journal of Applied Statistics, Vol. 33: 9, 1034, November 2006)
"... an important study tool for potential practitioners or all those researchers who study Bayesian methods through 'learning by doing'". (Statistical Papers,48,2007)
Book Information
ISBN 9780470863671
Author Peter E. Rossi
Format Hardback
Page Count 384
Imprint John Wiley & Sons Inc
Publisher John Wiley & Sons Inc
Weight(grams) 794g
Dimensions(mm) 255mm * 177mm * 27mm