Search Results - "Kutoyants, Yu. A."

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  1. 1

    Parameter Estimation for Continuous Time Hidden Markov Processes by Kutoyants, Yu. A.

    Published in Automation and remote control (01-03-2020)
    “…A survey of research works on the parameter estimation of hidden Markov processes is presented. Two observation models are considered: a partially observed…”
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    Journal Article
  2. 2

    Poisson source localization on the plane: the smooth case by Chernoyarov, O. V., Kutoyants, Yu. A.

    Published in Metrika (01-05-2020)
    “…We consider the problem of localization of a Poisson source using observations of inhomogeneous Poisson processes. We assume that k detectors are distributed…”
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    Journal Article
  3. 3

    Localization of two radioactive sources on the plane by Chernoyarov, O. V., Dachian, S., Farinetto, C., Kutoyants, Yu. A.

    “…The problem of localization on the plane of two radioactive sources by K detectors is considered. Each detector records a realization of an inhomogeneous…”
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  4. 4

    Poisson source localization on the plane: cusp case by Chernoyarov, O. V., Dachian, S., Kutoyants, Yu. A.

    “…This work is devoted to the problem of estimation of the localization of Poisson source. The observations are inhomogeneous Poisson processes registered by…”
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  5. 5

    Poisson source localization on the plane: change-point case by Farinetto, C., Kutoyants, Yu. A., Top, A.

    “…We present a detection problem where several spatially distributed sensors observe Poisson signals emitted from a single radioactive source of unknown…”
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  6. 6

    Estimation of the position and time of emission of a source by Chernoyarov, O. V., Dachian, S., Farinetto, C., Kutoyants, Yu. A.

    “…We consider the problem of the estimation of the position on the plane and of the moment of beginning of emission of a source by observations from  K detectors…”
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  7. 7

    On parameter estimation for cusp-type signals by Chernoyarov, O. V., Dachian, S., Kutoyants, Yu. A.

    “…We consider the problem of parameter estimation by continuous time observations of a deterministic signal in white Gaussian noise. It is supposed that the…”
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  8. 8

    On Estimation Errors in Optical Communication and Location by Chernoyarov, O. V., Dachian, S., Kutoyants, Yu. A., Zyulkov, A. V.

    Published in Automation and remote control (01-12-2021)
    “…We consider several problems of parameter estimation based on observations of inhomogeneous Poisson processes arising in various practical applications of…”
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  9. 9

    On multiple change-point estimation for Poisson process by Chernoyarov, O. V., Kutoyants, Yu. A., Top, A.

    “…This work is devoted to the problem of change-point parameter estimation in the case of the presence of multiple changes in the intensity function of the…”
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  10. 10

    On score-functions and goodness-of-fit tests for stochastic processes by Kutoyants, Yu. A.

    Published in Mathematical methods of statistics (01-04-2016)
    “…The problems of the construction of asymptotically distribution free goodness-of-fit tests for two diffusion processes are considered. The null hypothesis is…”
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  11. 11

    On hypothesis testing for Poisson processes: Regular case by Dachian, S., Kutoyants, Yu. A., Yang, L.

    “…We consider the problem of hypothesis testing in the situation when the firsthypothesis is simple and the second one is local one-sided composite. We describe…”
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  12. 12

    Estimation of cusp location of stochastic processes: a survey by Dachian, S., Kordzakhia, N., Kutoyants, Yu. A., Novikov, A.

    “…We present a review of some recent results on estimation of location parameter for several models of observations with cusp-type singularity at the change…”
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  13. 13

    Method of Moments Estimators and Multi–step MLE for Poisson Processes by Dabye, A. S., Gounoung, A. A., Kutoyants, Yu. A.

    “…We introduce two types of estimators of the finite–dimensional parameters in the case of observations of inhomogeneous Poisson processes. These are the…”
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  14. 14

    On hypothesis testing for Poisson processes. Singular cases by Dachian, S., Kutoyants, Yu. A., Yang, L.

    “…We consider the problem of hypothesis testing in the situation where the first hypothesis is simple and the second one is local one-sided composite. Wedescribe…”
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  15. 15

    On asymptotically distribution free tests with parametric hypothesis for ergodic diffusion processes by Kleptsyna, M., Kutoyants, Yu. A.

    “…We consider the problem of the construction of the asymptotically distribution free test by the observations of ergodic diffusion process. It is supposed that…”
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  16. 16

    Estimation in threshold autoregressive models with correlated innovations by Chigansky, P., Kutoyants, Yu. A.

    “…Large sample statistical analysis of threshold autoregressive models is usually based on the assumption that the underlying driving noise is uncorrelated. In…”
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  17. 17

    On the multi-step MLE-process for ergodic diffusion by Kutoyants, Yu.A.

    “…We propose a new method of the construction of the asymptotically efficient estimator-processes asymptotically equivalent to the MLE and the same time much…”
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  18. 18

    On nonlinear TAR processes and threshold estimation by Chigansky, P., Kutoyants, Yu. A.

    Published in Mathematical methods of statistics (01-04-2012)
    “…We consider the problem of threshold estimation for autoregressive time series with a “space switching” in the situation when the regression is nonlinear and…”
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  19. 19

    On multi-step MLE-process for Markov sequences by Kutoyants, Yu. A., Motrunich, A.

    Published in Metrika (01-08-2016)
    “…We consider the problem of the construction of the estimator-process of the unknown finite-dimensional parameter in the case of the observations of nonlinear…”
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  20. 20

    Nonparametric hypothesis testing for intensity of the poisson process by Ingster, Yu. I., Kutoyants, Yu. A.

    Published in Mathematical methods of statistics (01-09-2007)
    “…We propose a goodness-of-fit test for the hypothesis that the observed Poisson point process has a given periodic intensity function against a nonparametric…”
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