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Surveillance of a Simple Linear Regression

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  • Krieger A.M.
  • Pollak M.
  • Yakir B.

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  • Krieger A.M. & Pollak M. & Yakir B., 2003. "Surveillance of a Simple Linear Regression," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 456-469, January.
    • Handle: RePEc:bes:jnlasa:v:98:y:2003:p:456-469
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    Cited by:

    1. Moshe Pollak & Michal Shauly-Aharonov, 2019. "A Double Recursion for Calculating Moments of the Truncated Normal Distribution and its Connection to Change Detection," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 889-906, September.
    2. Frisén, Marianne, 2011. "Methods and evaluations for surveillance in industry, business, finance, and public health," Research Reports 2011:3, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    3. de Lima, Max Sousa & Duczmal, Luiz Henrique, 2014. "Adaptive likelihood ratio approaches for the detection of space–time disease clusters," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 352-370.
    4. Albert Vexler & Chengqing Wu & Kai Yu, 2010. "Optimal hypothesis testing: from semi to fully Bayes factors," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 71(2), pages 125-138, March.
    5. Frisén, Marianne, 2008. "Introduction to financial surveillance," Research Reports 2008:1, University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law.
    6. Albert Vexler & Sergey Tarima, 2011. "An optimal approach for hypothesis testing in the presence of incomplete data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(6), pages 1141-1163, December.

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