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Large and moderate deviations in testing Rayleigh diffusion model

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  • Nenghui Kuang
  • Huantian Xie

Abstract

This paper studies hypothesis testing in Rayleigh diffusion processes. With the help of large and moderate deviations for the log-likelihood ratio process, we give the negative regions and obtain the decay rates of the error probabilities. Copyright Springer-Verlag 2013

Suggested Citation

  • Nenghui Kuang & Huantian Xie, 2013. "Large and moderate deviations in testing Rayleigh diffusion model," Statistical Papers, Springer, vol. 54(3), pages 591-603, August.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:3:p:591-603
    DOI: 10.1007/s00362-012-0450-5
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    References listed on IDEAS

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    1. Gutiérrez, R. & Gutiérrez-Sánchez, R. & Nafidi, A., 2008. "Trend analysis and computational statistical estimation in a stochastic Rayleigh model: Simulation and application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(2), pages 209-217.
    2. Pavel Gapeev & Uwe Küchler, 2008. "On large deviations in testing Ornstein–Uhlenbeck-type models," Statistical Inference for Stochastic Processes, Springer, vol. 11(2), pages 143-155, June.
    3. Hamzeh Torabi & Javad Behboodian, 2007. "Likelihood ratio tests for fuzzy hypotheses testing," Statistical Papers, Springer, vol. 48(3), pages 509-522, September.
    4. Zhao, Shoujiang & Gao, Fuqing, 2010. "Large deviations in testing Jacobi model," Statistics & Probability Letters, Elsevier, vol. 80(1), pages 34-41, January.
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    Cited by:

    1. Hui Jiang & Jin Shao & Qingshan Yang, 2021. "Sharp large deviations for a class of normalized L-statistics and applications," Statistical Papers, Springer, vol. 62(2), pages 721-744, April.

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