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Teoriya Veroyatnostei i ee Primeneniya, 2018, Volume 63, Issue 2, Pages 211–239
DOI: https://doi.org/10.4213/tvp5141
(Mi tvp5141)
 

This article is cited in 6 scientific papers (total in 6 papers)

On estimation of parameters in the case of discontinuous densities

A. A. Borovkovab

a Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk
b Novosibirsk State University
Full-text PDF (615 kB) Citations (6)
References:
Abstract: This paper is concerned with the problem of construction of estimators of parameters in the case when the density fθ(x) of the distribution Pθ of a sample X of size n has at least one point of discontinuity x(θ), x(θ)0. It is assumed that either (a) from a priori considerations one can specify a localization of the parameter θ (or points of discontinuity) satisfying easily verifiable conditions, or (b) there exists a consistent estimator ˜θ of the parameter θ (possibly constructed from the same sample X), which also provides some localization. Then a simple rule is used to construct, from the segment of the empirical distribution function defined by the localization, a family of estimators θg that depends on the parameter g such that (1) for sufficiently large n, the probabilities P(θgθ>v/n) and P(θgθ<v/n) can be explicitly estimated by a v-exponential bound; (2) in case (b) under suitable conditions (see conditions I–IV in Chap. 5 of [I. A. Ibragimov and R. Z. Has'minskiĭ, Statistical Estimation. Asymptotic Theory, Springer, New York, 1981], where maximum likelihood estimators were studied), a value of g can be given such that the estimator θg is asymptotically equivalent to the maximum likelihood estimator ˆθ; i.e., Pθ(n(θgθ)>v)Pθ(n(ˆθθ)>v) for any v and n; (3) the value of g can be chosen so that the inequality Eθ(θgθ)2<Eθ(ˆθθ)2 is possible for sufficiently large n. Effectively no smoothness conditions are imposed on fθ(x). With an available “auxiliary” consistent estimator ˜θ, simple rules are suggested for finding estimators θg which are asymptotically equivalent to ˆθ. The limiting distribution of n(θgθ) as n is studied.
Keywords: estimators of parameters, maximum likelihood estimator, distribution with discontinuous density, change-point problem, infinitely divisible factorization.
Received: 23.03.2017
Revised: 03.04.2017
Accepted: 29.08.2017
English version:
Theory of Probability and its Applications, 2018, Volume 63, Issue 2, Pages 169–192
DOI: https://doi.org/10.1137/S0040585X97T98899X
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. A. Borovkov, “On estimation of parameters in the case of discontinuous densities”, Teor. Veroyatnost. i Primenen., 63:2 (2018), 211–239; Theory Probab. Appl., 63:2 (2018), 169–192
Citation in format AMSBIB
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\jour Teor. Veroyatnost. i Primenen.
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\pages 211--239
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\transl
\jour Theory Probab. Appl.
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\pages 169--192
\crossref{https://doi.org/10.1137/S0040585X97T98899X}
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  • https://doi.org/10.4213/tvp5141
  • https://www.mathnet.ru/eng/tvp/v63/i2/p211
  • This publication is cited in the following 6 articles:
    1. C. S. Philipps, “The MLE of Aigner, Amemiya, and Poirier is not the expectile MLE”, Econometric Reviews, 41:1 (2022), 99  crossref  mathscinet
    2. V. E. Mosyagin, “Asymptotics for the distribution of the time of attaining the maximum for a trajectory of a Poisson process with linear drift and intensity switch”, Theory Probab. Appl., 66:2 (2021), 75–88  mathnet  crossref  crossref  mathscinet  zmath  isi
    3. I. G. Kazantsev, B. O. Mukhametzhanova, K. T. Iskakov, “Detection of the corner structures in 3D arrays using scalable masks”, Sib. elektron. matem. izv., 18:1 (2021), 61–71  mathnet  crossref
    4. I. G. Kazantsev, B. O. Mukhametzhanova, K. T. Iskakov, T. Mirgalikyzy, “Detection of the corner structures in images by scalable masks”, J. Appl. Industr. Math., 14:1 (2020), 73–84  mathnet  crossref  crossref
    5. Collin Philipps, “The MLE of Aigner, Amemiya, and Poirier is not the Expectile MLE”, SSRN Journal, 2020  crossref
    6. V. E. Mosyagin, “Exact asymptotics for the distribution of the time of attaining the maximum for a trajectory of a compound Poisson process with linear drift”, Siberian Adv. Math., 30:1 (2020), 26–42  mathnet  crossref  crossref
    Citing articles in Google Scholar: Russian citations, English citations
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    Теория вероятностей и ее применения Theory of Probability and its Applications
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