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On parameter estimation for cusp-type signals

Author

Listed:
  • O. V. Chernoyarov

    (National Research University “MPEI”)

  • S. Dachian

    (National Research University “MPEI”
    Laboratoire Paul Painlevé, UMR CNRS 8524, Cité Scientifique)

  • Yu. A. Kutoyants

    (National Research University “MPEI”
    Université du Maine)

Abstract

We consider the problem of parameter estimation by continuous time observations of a deterministic signal in white Gaussian noise. It is supposed that the signal has a cusp-type singularity. The properties of the maximum-likelihood and Bayesian estimators are described in the asymptotics of small noise. Special attention is paid to the problem of parameter estimation in the situation of misspecification in regularity, i.e., when the statistician supposes that the observed signal has this singularity, but the real signal is smooth. The rate and the asymptotic distribution of the maximum-likelihood estimator in this situation are described.

Suggested Citation

  • O. V. Chernoyarov & S. Dachian & Yu. A. Kutoyants, 2018. "On parameter estimation for cusp-type signals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(1), pages 39-62, February.
    • Handle: RePEc:spr:aistmt:v:70:y:2018:i:1:d:10.1007_s10463-016-0581-x
    DOI: 10.1007/s10463-016-0581-x
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    References listed on IDEAS

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    1. Prakasa Rao, B. L. S., 2004. "Estimation of cusp in nonregular nonlinear regression models," Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 243-251, February.
    2. Fujii, Takayuki, 2010. "An extension of cusp estimation problem in ergodic diffusion processes," Statistics & Probability Letters, Elsevier, vol. 80(9-10), pages 779-783, May.
    3. S. Dachian, 2003. "Estimation of Cusp Location by Poisson Observations," Statistical Inference for Stochastic Processes, Springer, vol. 6(1), pages 1-14, January.
    4. Rao, B. L. S. Prakasa, 1985. "Asymptotic theory of least squares estimator in a nonregular nonlinear regression model," Statistics & Probability Letters, Elsevier, vol. 3(1), pages 15-18, February.
    5. Maik Döring & Uwe Jensen, 2015. "Smooth change point estimation in regression models with random design," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(3), pages 595-619, June.
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    Cited by:

    1. Kordzakhia, Nino E. & Kutoyants, Yury A. & Novikov, Alexander A. & Hin, Lin-Yee, 2018. "On limit distributions of estimators in irregular statistical models and a new representation of fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 139(C), pages 141-151.
    2. S. Dachian & N. Kordzakhia & Yu. A. Kutoyants & A. Novikov, 2018. "Estimation of cusp location of stochastic processes: a survey," Statistical Inference for Stochastic Processes, Springer, vol. 21(2), pages 345-362, July.
    3. O. V. Chernoyarov & S. Dachian & Yu. A. Kutoyants, 2020. "Poisson source localization on the plane: cusp case," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(5), pages 1137-1157, October.

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