Divergence measures and weak majorization in estimation problems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F14%3A86091093" target="_blank" >RIV/61989100:27510/14:86091093 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Divergence measures and weak majorization in estimation problems
Original language description
Statistical inference can be interpreted as a problem of minimum distance between an empirical (observed) and a theoretical distribution. The most used measures of dissimilarity/disparity between probability distributions are the well known divergence measures. These measures are not symmetric: basing on the duality in their formulation, we classify divergences within the context of estimation into two main classes and analyze them with reference to majorization theory. In this regard, the consistency of divergence measures with respect to the generalized (strong) majorization pre-order is can be easily derived from a well known characterization theorem. Nevertheless, in many practical contexts such as estimation problem, one of the main assumption for(strong) majorization could be unfulfilled. Thus we study under which conditions divergence measures are consistent with respect to the generalization of weak majorization (from above). This paper provides a guideline for the choice of a
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Result continuities
Project
<a href="/en/project/EE2.3.30.0016" target="_blank" >EE2.3.30.0016: Opportunities for young researchers</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2nd International Conference on Mathematical, Computational and Statistical Sciences (MCSS '14); Proceedings of the 7th International Conference on Finite Difference...: Gdansk, Poland May 15-17, 2014
ISBN
978-960-474-380-3
ISSN
2227-4588
e-ISSN
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Number of pages
6
Pages from-to
152-157
Publisher name
WSEAS Press
Place of publication
Cambridge
Event location
Gdaňsk
Event date
May 25, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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