Statistical Estimations of Lattice-Valued Possibilistic Distributions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00361642" target="_blank" >RIV/67985807:_____/11:00361642 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-642-22152-1_58" target="_blank" >http://dx.doi.org/10.1007/978-3-642-22152-1_58</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-22152-1_58" target="_blank" >10.1007/978-3-642-22152-1_58</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Statistical Estimations of Lattice-Valued Possibilistic Distributions

Popis výsledku v původním jazyce

The most often applied non-numerical uncertainty degrees are those taking their values in complete lattices, but also their weakened versions may be of interest. In what follows, we introduce and analyze possibilistic distributions and measures taking values in finite upper-valued possibilistic lattices, so that only for finite sets of such values their supremum is defined. For infinite sets of values of the finite lattice in question we apply the idea of the so called Monte-Carlo method: sample at random and under certain conditions a large enough finite subset of the infinite set in question, and take the supremum over this finite sample set as a "good enough" estimation of the undefined supremum of the infinite set. A number of more or less easy toprove assertions demonstrate the conditions when and in which sense the quality of the results obtained by replacing non-existing or non-accessible supremum values by their random estimations tend to the optimum results supposing that the

Název v anglickém jazyce

Statistical Estimations of Lattice-Valued Possibilistic Distributions

Popis výsledku anglicky

The most often applied non-numerical uncertainty degrees are those taking their values in complete lattices, but also their weakened versions may be of interest. In what follows, we introduce and analyze possibilistic distributions and measures taking values in finite upper-valued possibilistic lattices, so that only for finite sets of such values their supremum is defined. For infinite sets of values of the finite lattice in question we apply the idea of the so called Monte-Carlo method: sample at random and under certain conditions a large enough finite subset of the infinite set in question, and take the supremum over this finite sample set as a "good enough" estimation of the undefined supremum of the infinite set. A number of more or less easy toprove assertions demonstrate the conditions when and in which sense the quality of the results obtained by replacing non-existing or non-accessible supremum values by their random estimations tend to the optimum results supposing that the

Druh

D - Stať ve sborníku

CEP obor

BA - Obecná matematika

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název statě ve sborníku

Symbolic and Quantitative Approaches to Reasoning with Uncertainty

ISBN

978-3-642-22151-4

ISSN

—

e-ISSN

—

Počet stran výsledku

12

Strana od-do

688-699

Název nakladatele

Springer

Místo vydání

Heidelberg

Místo konání akce

Belfast

Datum konání akce

29. 6. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—