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Avtomatika i Telemekhanika, 2010, Issue 3, Pages 98–116 (Mi at793)  
This article is cited in 14 scientific papers (total in 14 papers)

Processing of Experimental Data

Separating mixtures of probability distributions with the grid method of moments and the grid maximal likelihood method

V. Yu. Korolevab, A. L. Nazarova

a M. V. Lomonosov Moscow State University
b Institute of Informatics Problems, Russian Academy of Sciences, Moscow, Russia
Full-text PDF (664 kB) Citations (14)
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Abstract: We consider the so-called grid methods for approximate statistical separation of probability distribution mixtures based on (i) minimizing the disparity between theoretical and empirical moments and (ii) maximizing the grid likelihood function. We show that problems of type (i) can be reduced to linear programming problems. For a numerical solution of problems of type (ii) we offer the “truncated” EM algorithm and the conditional gradient algorithm. We show results of a comparative study of the suggested approaches' efficiency based on solving the decomposition problem for the volatility function of financial indices. We give examples of volatility decompositions for the CAC 40 index.
Presented by the member of Editorial Board: A. I. Kibzun

Received: 02.03.2009
English version:
Automation and Remote Control, 2010, Volume 71, Issue 3, Pages 455–472
DOI: https://doi.org/10.1134/S0005117910030082
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: V. Yu. Korolev, A. L. Nazarov, “Separating mixtures of probability distributions with the grid method of moments and the grid maximal likelihood method”, Avtomat. i Telemekh., 2010, no. 3, 98–116; Autom. Remote Control, 71:3 (2010), 455–472
Citation in format AMSBIB
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    • This publication is cited in the following 14 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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