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A Bayesian approach to retrospective identification of change-points

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  • Booth, N.B.
  • Smith, A.F.M.

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  • Booth, N.B. & Smith, A.F.M., 1982. "A Bayesian approach to retrospective identification of change-points," Journal of Econometrics, Elsevier, vol. 19(1), pages 7-22, May.
    • Handle: RePEc:eee:econom:v:19:y:1982:i:1:p:7-22
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    Cited by:

    1. Stephan, Paula E., 2010. "The Economics of Science," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 217-273, Elsevier.
    2. Minya Xu & Ping-Shou Zhong & Wei Wang, 2016. "Detecting Variance Change-Points for Blocked Time Series and Dependent Panel Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 213-226, April.
    3. Corneo, Giacomo & Jeanne, Olivier, 2001. "On relative-wealth effects and long-run growth," Research in Economics, Elsevier, vol. 55(4), pages 349-358, December.
    4. Galeano, Pedro & Peña, Daniel, 2004. "Variance changes detection in multivariate time series," DES - Working Papers. Statistics and Econometrics. WS ws041305, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Maria Barbieri & Caterina Conigliani, 1998. "Bayesian analysis of autoregressive time series with change points," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 7(3), pages 243-255, December.
    6. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.

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