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Le Cam theorem on interval division by randomly chosen points: Pedagogical explanations and application to temporal cluster detection

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  • Christophe Demattei

Abstract

The aim of this paper is to propose a pedagogical explanation of the Le Cam theorem and to illustrate its use, through a practical application, for temporal cluster detection. This theorem focusses on the interval division by randomly chosen points. The aim of the theorem is to characterize the asymptotic behavior of a certain category of sums of functions applied to the length of successive intervals between points. It is not very intuitive and its understanding needs some deepening. After enouncing the theorem, its different aspects are explained and detailed in a way as pedagogical as possible. Theoretical applications are proposed through the proof of two propositions. Then a very concrete application of this theorem for temporal cluster detection is presented, tested by a power study, and compared with other global cluster detection tests. Finally, this approach is applied to the well-known Knox temporal data set.

Suggested Citation

  • Christophe Demattei, 2010. "Le Cam theorem on interval division by randomly chosen points: Pedagogical explanations and application to temporal cluster detection," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(3), pages 415-424.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:3:p:415-424
    DOI: 10.1080/02664760802715872
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    References listed on IDEAS

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    1. Nicolas Molinari & Chistophe Bonaldi & Jean-Pierre Daurés, 2001. "Multiple Temporal Cluster Detection," Biometrics, The International Biometric Society, vol. 57(2), pages 577-583, June.
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