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Large deviation principle in nonparametric estimation of marked point processes

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  • Florens, Danielle
  • Pham, Huyên

Abstract

The nonparametric estimation problem of intensity measure of a homogeneous Poisson random measure is considered, based on an eventually partial observation of the jumps amplitude. We prove a large deviation principle for a kernel type estimator and we explicitly identify its rate function.

Suggested Citation

  • Florens, Danielle & Pham, Huyên, 1999. "Large deviation principle in nonparametric estimation of marked point processes," Statistics & Probability Letters, Elsevier, vol. 41(4), pages 383-388, February.
    • Handle: RePEc:eee:stapro:v:41:y:1999:i:4:p:383-388
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    References listed on IDEAS

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    1. Ellis, Steven P., 1991. "Density estimation for point processes," Stochastic Processes and their Applications, Elsevier, vol. 39(2), pages 345-358, December.
    2. Florens, Danielle & Pham, Huyên, 1998. "Large deviation probabilities in estimation of Poisson random measures," Stochastic Processes and their Applications, Elsevier, vol. 76(1), pages 117-139, August.
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