The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p
[Wiley Series in Probability and Statistics] Bayesian Statistics and Marketing (Rossi/Bayesian Statistics and Marketing) || Bayesm MCMC Functions & Key Bayesm Utilities
β Scribed by Rossi, Peter E.; Allenby, Greg M.; McCulloch, Robert
- Publisher
- John Wiley & Sons, Ltd
- Year
- 2006
- Tongue
- English
- Weight
- 108 KB
- Edition
- 1
- Category
- Article
- ISBN
- 0470863676
No coin nor oath required. For personal study only.
β¦ Synopsis
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources.
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 authorsβ 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 bookβs website hosts datasets and R code for the case studies.
Bayesian Statistics and Marketing provides a platform for researchers in marketing to analyse their data with state-of-the-art methods and develop new models of consumer behaviour. It provides a unified reference for cutting-edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.
π SIMILAR VOLUMES
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p
The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new p
An R package is a collection of functions, data sets and documentation which can be easily installed and updated from within R. The package resides on the CRAN network of world-wide mirror sites so that its availability is assured. bayesm is an R package that implement the methods in this book. The