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Teoriya Veroyatnostei i ee Primeneniya, 1999, Volume 44, Issue 1, Pages 138–143
DOI: https://doi.org/10.4213/tvp607
(Mi tvp607)
 

This article is cited in 1 scientific paper (total in 1 paper)

Short Communications

On convergence in law of maxima of independent identically distributed random variables with random coefficients

A. N. Chuprunov

N. G. Chebotarev Research Institute of Mathematics and Mechanics, Kazan State University
Full-text PDF (890 kB) Citations (1)
Abstract: This paper provides limit theorems for maxima of independent identically distributed random variables which belong to the domain of normal attraction of a max-stable variable and have random coefficients with the property of asymptotic negligibility or its analogues. The convergence of random step-functions determined by those maxima is studied in the Skorokhod space. The limit distributions are indicated.
Keywords: independent identically distributed random variables, convergence in law, functional limit theorem, invariance principle, max-stable distributions.
Received: 20.11.1996
English version:
Theory of Probability and its Applications, 2000, Volume 44, Issue 1, Pages 93–97
DOI: https://doi.org/10.1137/S0040585X97977434
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. N. Chuprunov, “On convergence in law of maxima of independent identically distributed random variables with random coefficients”, Teor. Veroyatnost. i Primenen., 44:1 (1999), 138–143; Theory Probab. Appl., 44:1 (2000), 93–97
Citation in format AMSBIB
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\paper On convergence in law of maxima of independent identically distributed random variables with random coefficients
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\pages 138--143
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\jour Theory Probab. Appl.
\yr 2000
\vol 44
\issue 1
\pages 93--97
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  • https://www.mathnet.ru/eng/tvp607
  • https://doi.org/10.4213/tvp607
  • https://www.mathnet.ru/eng/tvp/v44/i1/p138
  • This publication is cited in the following 1 articles:
    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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