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  • 标题:bcp: An R Package for Performing a Bayesian Analysis of Change Point Problems
  • 本地全文:下载
  • 作者:Chandra Erdman ; John W. Emerson
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2007
  • 卷号:23
  • 期号:1
  • 页码:1-13
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:Barry and Hartigan (1993) propose a Bayesian analysis for change point problems. We provide a brief summary of selected work on change point problems, both preceding and following Barry and Hartigan. We outline Barry and Hartigan's approach and offer a new R package, bcp (Erdman and Emerson 2007), implementing their analysis. We discuss two frequentist alternatives to the Bayesian analysis, the recursive circular binary segmentation algorithm (Olshen and Venkatraman 2004) and the dynamic programming algorithm of (Bai and Perron 2003). We illustrate the application of bcp with economic and microarray data from the literature.
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