EMPIRICAL ESTIMATES IN STOCHASTIC PROGRAMS WITH PROBABILITY AND SECOND ORDER STOCHASTIC DOMINANCE CONSTRAINTS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00454495" target="_blank" >RIV/67985556:_____/15:00454495 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

EMPIRICAL ESTIMATES IN STOCHASTIC PROGRAMS WITH PROBABILITY AND SECOND ORDER STOCHASTIC DOMINANCE CONSTRAINTS

Popis výsledku v původním jazyce

Stochastic optimization problems with an operator of the mathematical expectation in the objective function, probability and stochastic dominance constraints belong to ?deterministic problems depending on a probability measure. Complete knowledge of theprobability measure is a necessary condition for solving these problems. However, since this assumption is very rarely fulfilled (in applications), problems are mostly solved on the basis of data. Mathematically it means that the ?underlying probabilitymeasure is replaced by an empirical one (determined by the corresponding data). Stochastic estimates of an optimal value and an optimal solution can only then be obtained. Properties of these estimates have been investigated many times, mostly in the case of constraint sets not depending on the probability measure. Our results generalize such estimates to two separate cases (already mentioned above) when the constraint sets do depend on the probability measure.

Název v anglickém jazyce

EMPIRICAL ESTIMATES IN STOCHASTIC PROGRAMS WITH PROBABILITY AND SECOND ORDER STOCHASTIC DOMINANCE CONSTRAINTS

Popis výsledku anglicky

Stochastic optimization problems with an operator of the mathematical expectation in the objective function, probability and stochastic dominance constraints belong to ?deterministic problems depending on a probability measure. Complete knowledge of theprobability measure is a necessary condition for solving these problems. However, since this assumption is very rarely fulfilled (in applications), problems are mostly solved on the basis of data. Mathematically it means that the ?underlying probabilitymeasure is replaced by an empirical one (determined by the corresponding data). Stochastic estimates of an optimal value and an optimal solution can only then be obtained. Properties of these estimates have been investigated many times, mostly in the case of constraint sets not depending on the probability measure. Our results generalize such estimates to two separate cases (already mentioned above) when the constraint sets do depend on the probability measure.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

<a href="/cs/project/GA13-14445S" target="_blank" >GA13-14445S: Nové trendy ve stochastických ekonomických modelech za neurčitosti</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Acta Mathematica Universitas Comenianae

ISSN

0862-9544

e-ISSN

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Svazek periodika

84

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

15

Strana od-do

267-281

Kód UT WoS článku

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EID výsledku v databázi Scopus

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