Estimation of a regression with the pulse type noise from discrete data

V. V. Konev, E. A. Pchelintsev, S. M. Pergamenshchikov

    Результат исследований: Материалы для журналаСтатья

    10 Цитирования (Scopus)


    This paper considers the problem of estimating parameters in a periodic regression in continuous time with a semimartingale noise by discrete time observations. Improved estimates for the regression parameters are proposed. It is established that under some general conditions these estimates have an advantage in the mean square accuracy over the least squares estimates. The asymptotic minimaxity of the improved estimates has been proved in the robust risk sense. The properties of the proposed procedure for the models with non-Gaussian noises of pulse type have been studied. The pulse disturbances have random intensity and occur at random times which form a Poisson process.

    Язык оригиналаАнглийский
    Страницы (с-по)442-457
    Число страниц16
    ЖурналTheory of Probability and its Applications
    Номер выпуска3
    СостояниеОпубликовано - 2014

    ASJC Scopus subject areas

    • Statistics and Probability
    • Statistics, Probability and Uncertainty

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