贝叶斯概率
贝叶斯统计
计算机科学
灵活性(工程)
模块化(生物学)
营销
变阶贝叶斯网络
数据科学
贝叶斯计量经济学
贝叶斯推理
人工智能
统计
数学
业务
生物
遗传学
作者
Peter E. Rossi,Greg M. Allenby
出处
期刊:Marketing Science
[Institute for Operations Research and the Management Sciences]
日期:2003-08-01
卷期号:22 (3): 304-328
被引量:1218
标识
DOI:10.1287/mksc.22.3.304.17739
摘要
Bayesian methods have become widespread in marketing literature. We review the essence of the Bayesian approach and explain why it is particularly useful for marketing problems. While the appeal of the Bayesian approach has long been noted by researchers, recent developments in computational methods and expanded availability of detailed marketplace data has fueled the growth in application of Bayesian methods in marketing. We emphasize the modularity and flexibility of modern Bayesian approaches. The usefulness of Bayesian methods in situations in which there is limited information about a large number of units or where the information comes from different sources is noted. We include an extensive discussion of open issues and directions for future research.
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