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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F13%3A00393989%21RIV14-GA0-67985556
rdf:type
n9:Vysledek skos:Concept
dcterms:description
Every process in our environment can be described with a statistical model containing inner properties expressed by parameters. These are usually unknown and the determination of their values is of interest in the statistical branch called parameter estimation. This branch involves many methods solving different estimation cases, e.g. the estimation of location and scale parameters. To obtain the parameter estimate we exploit the data given by data sources. In particular, the estimate is their combination. Improvement of the parameter estimates involve the assignment of the weights to the data sources resulting in a weighted combination of data. In this paper we focus on the derivation of the weights arisen within the Supra-Bayesian approach and on the simulation study of their behaviour and the behaviour of the final estimate. Every process in our environment can be described with a statistical model containing inner properties expressed by parameters. These are usually unknown and the determination of their values is of interest in the statistical branch called parameter estimation. This branch involves many methods solving different estimation cases, e.g. the estimation of location and scale parameters. To obtain the parameter estimate we exploit the data given by data sources. In particular, the estimate is their combination. Improvement of the parameter estimates involve the assignment of the weights to the data sources resulting in a weighted combination of data. In this paper we focus on the derivation of the weights arisen within the Supra-Bayesian approach and on the simulation study of their behaviour and the behaviour of the final estimate.
dcterms:title
On Supra-Bayesian weighted combination of available data determined by Kerridge inaccuracy ane entropy On Supra-Bayesian weighted combination of available data determined by Kerridge inaccuracy ane entropy
skos:prefLabel
On Supra-Bayesian weighted combination of available data determined by Kerridge inaccuracy ane entropy On Supra-Bayesian weighted combination of available data determined by Kerridge inaccuracy ane entropy
skos:notation
RIV/67985556:_____/13:00393989!RIV14-GA0-67985556
n9:predkladatel
n10:ico%3A67985556
n4:aktivita
n6:I n6:P
n4:aktivity
I, P(GA13-13502S)
n4:cisloPeriodika
1
n4:dodaniDat
n7:2014
n4:domaciTvurceVysledku
n12:2844737
n4:druhVysledku
n18:J
n4:duvernostUdaju
n15:S
n4:entitaPredkladatele
n16:predkladatel
n4:idSjednocenehoVysledku
93826
n4:idVysledku
RIV/67985556:_____/13:00393989
n4:jazykVysledku
n13:eng
n4:klicovaSlova
Kerridge inaccuracy; maximum entropy principle; parameter estimation
n4:klicoveSlovo
n11:Kerridge%20inaccuracy n11:maximum%20entropy%20principle n11:parameter%20estimation
n4:kodStatuVydavatele
BG - Bulharská republika
n4:kontrolniKodProRIV
[56F88EC96E65]
n4:nazevZdroje
Pliska Studia Mathematica Bulgarica
n4:obor
n5:BD
n4:pocetDomacichTvurcuVysledku
1
n4:pocetTvurcuVysledku
1
n4:projekt
n17:GA13-13502S
n4:rokUplatneniVysledku
n7:2013
n4:svazekPeriodika
22
n4:tvurceVysledku
Sečkárová, Vladimíra
s:issn
0204-9805
s:numberOfPages
10