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Teoriya Veroyatnostei i ee Primeneniya, 1973, Volume 18, Issue 1, Pages 78–93 (Mi tvp2682)  

This article is cited in 38 scientific papers (total in 39 papers)

Asymptotical behaviour of some statistical estimators. II. Limiting theorems for the a posteriory density and Bayesian estimators

I. A. Ibragimov, R. Z. Khas'minskii

Moscow
Abstract: In the second part of the paper we use propositions, methods and results of the first part appeared in the previous issue of this journal.
Under conditions I–IV of § 1, we prove theorems about behaviour of the a posteriory density (similar to the well-known Le Cam's results [2]), Bayesian estimators t(a)n for the risk function θa, Pitman's estimators of the location parameter etc. We prove, for example, that the estimators t(a)n, for different a1, are equivalent in the sense that
\mathbf E\{\sqrt n\bigl|t_n^{(a_1)}-t_n^{(a_2)}\bigr|\}^p\underset{n\to\infty}\longrightarrow0\quad(p>0).
Received: 05.01.1971
English version:
Theory of Probability and its Applications, 1973, Volume 18, Issue 1, Pages 76–91
DOI: https://doi.org/10.1137/1118006
Bibliographic databases:
Language: Russian
Citation: I. A. Ibragimov, R. Z. Khas'minskii, “Asymptotical behaviour of some statistical estimators. II. Limiting theorems for the a posteriory density and Bayesian estimators”, Teor. Veroyatnost. i Primenen., 18:1 (1973), 78–93; Theory Probab. Appl., 18:1 (1973), 76–91
Citation in format AMSBIB
\Bibitem{IbrKha73}
\by I.~A.~Ibragimov, R.~Z.~Khas'minskii
\paper Asymptotical behaviour of some statistical estimators. II.~Limiting theorems for the a posteriory density and Bayesian estimators
\jour Teor. Veroyatnost. i Primenen.
\yr 1973
\vol 18
\issue 1
\pages 78--93
\mathnet{http://mi.mathnet.ru/tvp2682}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=311009}
\zmath{https://zbmath.org/?q=an:0283.62038}
\transl
\jour Theory Probab. Appl.
\yr 1973
\vol 18
\issue 1
\pages 76--91
\crossref{https://doi.org/10.1137/1118006}
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  • https://www.mathnet.ru/eng/tvp/v18/i1/p78
    Cycle of papers
    This publication is cited in the following 39 articles:
    1. Nakahiro Yoshida, “Simplified quasi-likelihood analysis for a locally asymptotically quadratic random field”, Ann Inst Stat Math, 2024  crossref
    2. A. A. Borovkov, Al. V. Bulinski, A. M. Vershik, D. Zaporozhets, A. S. Holevo, A. N. Shiryaev, “Ildar Abdullovich Ibragimov (on his ninetieth birthday)”, Russian Math. Surveys, 78:3 (2023), 573–583  mathnet  crossref  crossref  mathscinet  adsnasa  isi
    3. Nakahiro Yoshida, “Quasi-likelihood analysis and its applications”, Stat Inference Stoch Process, 25:1 (2022), 43  crossref
    4. F. Götze, A. Yu. Zaitsev, “Rare Events and Poisson Point Processes”, J Math Sci, 244:5 (2020), 771  crossref
    5. Rudolf Ahlswede, Foundations in Signal Processing, Communications and Networking, 15, Probabilistic Methods and Distributed Information, 2019, 533  crossref
    6. A. A. Zaikin, “Estimates with asymptotically uniformly minimal d-risk”, Theory Probab. Appl., 63:3 (2019), 500–505  mathnet  crossref  crossref  isi  elib
    7. Yusuke Kaino, Masayuki Uchida, “Hybrid estimators for small diffusion processes based on reduced data”, Metrika, 81:7 (2018), 745  crossref
    8. Kamil Dedecius, Vladimira Seckarova, “Factorized Estimation of Partially Shared Parameters in Diffusion Networks”, IEEE Trans. Signal Process., 65:19 (2017), 5153  crossref
    9. Kamil Dedecius, Petar M. Djuric, “Sequential Estimation and Diffusion of Information Over Networks: A Bayesian Approach With Exponential Family of Distributions”, IEEE Trans. Signal Process., 65:7 (2017), 1795  crossref
    10. A. A. Zaikin, “Asymptotic expansion of posterior distribution of parameter centered by a \sqrt n-consistent estimate”, J. Math. Sci. (N. Y.), 229:6 (2018), 678–697  mathnet  crossref  mathscinet
    11. George Monokroussos, “A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series”, Comput Econ, 42:1 (2013), 71  crossref
    12. George Monokroussos, “A Classical MCMC Approach to the Estimation of Limited Dependent Variable Models of Time Series”, SSRN Journal, 2012  crossref
    13. M. C. M. de Gunst, O. Shcherbakova, “Asymptotic behavior of Bayes estimators for hidden Markov models with application to ion channels”, Math. Meth. Stat., 17:4 (2008), 342  crossref
    14. Shyang Chang, Yen-Ching Chang, Chen-Yu Chang, “A minimum discrepancy estimator in parameter estimation”, IEEE Trans. Inform. Theory, 44:7 (1998), 2930  crossref
    15. Nakahiro Yoshida, “Estimation for diffusion processes from discrete observation”, Journal of Multivariate Analysis, 41:2 (1992), 220  crossref
    16. E. L. Lehmann, Theory of Point Estimation, 1991, 403  crossref
    17. Murray D. Burke, Edit Gombay, “The bootstrapped maximum likelihood estimator with an application”, Statistics & Probability Letters, 12:5 (1991), 421  crossref
    18. Nakahiro Yoshida, “Asymptotic behavior of M-estimator and related random field for diffusion process”, Ann Inst Stat Math, 42:2 (1990), 221  crossref
    19. Jan Hanousek, “Asymptotic relation of M- and P-estimators of location”, Computational Statistics & Data Analysis, 6:3 (1988), 277  crossref
    20. Ya'acov Ritov, “Asymptotic results in robust quasi-bayesian estimation”, Journal of Multivariate Analysis, 23:2 (1987), 290  crossref
    Citing articles in Google Scholar: Russian citations, English citations
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