Stochastic Convergences in Divergences
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F10%3A00176068" target="_blank" >RIV/68407700:21340/10:00176068 - 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
Stochastic Convergences in Divergences
Original language description
The paper presents a new unifying look at the statistical inference. We define score functions and minimum score estimators. We show that the stochastic convergence for estimators, i.e. the consistency of an estimators in score functions, leads to various types of consistency in the well-known statistical distances or disparity measures between probability distributions. We formulate conditions under which a score function is phi-divergence of theoretical and empirical distribution. Conversely, each phi-divergence is a score function. We prove that minimization of arbitrary divergence score function leads to the classical histogram density estimator and that a special score function leads in a similar sense to the minimum Kolmogorov distance estimator.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
SPMS 2010 Stochastic and Physical Monitoring Systems
ISBN
978-80-01-04641-8
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
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Publisher name
ČVUT
Place of publication
Praha
Event location
Děčín
Event date
Jun 27, 2010
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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