Performance of Kullback-Leibler Based Expert Opinion Pooling for Unlikely Events

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00479432" target="_blank" >RIV/67985556:_____/17:00479432 - 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

Performance of Kullback-Leibler Based Expert Opinion Pooling for Unlikely Events

Popis výsledku v původním jazyce

The aggregation of available information is of great importance in many branches of economics,nsocial sciences. Often, we can only rely on experts’ opinions, i.e. probabilities assigned to possible events. To deal with opinions in probabilistic form, we focus on the Kullback-Leibler (KL) divergence based pools: linear, logarithmic and KL-pool (Seckarova, 2015). Since occurrence of events is subject to random influences of the real world, it is important to address events assigned lower probabilities (unlikely events). This is done by choosing pooling with a higher entropy than standard linear or logarithmic options, i.e. the KL-pool. We show how well the mentioned pools perform on real data using absolute error, KL-divergence and quadratic reward. In cases favoring events assigned higher probabilities, the KL-pool performs similarly to the linear pool and outperforms the logarithmic pool. When unlikely events occur, the KL-pool outperforms both pools, which makes it a reasonable way of pooling.n

Název v anglickém jazyce

Performance of Kullback-Leibler Based Expert Opinion Pooling for Unlikely Events

Popis výsledku anglicky

The aggregation of available information is of great importance in many branches of economics,nsocial sciences. Often, we can only rely on experts’ opinions, i.e. probabilities assigned to possible events. To deal with opinions in probabilistic form, we focus on the Kullback-Leibler (KL) divergence based pools: linear, logarithmic and KL-pool (Seckarova, 2015). Since occurrence of events is subject to random influences of the real world, it is important to address events assigned lower probabilities (unlikely events). This is done by choosing pooling with a higher entropy than standard linear or logarithmic options, i.e. the KL-pool. We show how well the mentioned pools perform on real data using absolute error, KL-divergence and quadratic reward. In cases favoring events assigned higher probabilities, the KL-pool performs similarly to the linear pool and outperforms the logarithmic pool. When unlikely events occur, the KL-pool outperforms both pools, which makes it a reasonable way of pooling.n

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA16-09848S" target="_blank" >GA16-09848S: Racionalita a uvažování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the NIPS 2016 Workshop on Imperfect Decision Makers

ISBN

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ISSN

1938-7228

e-ISSN

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Počet stran výsledku

10

Strana od-do

41-50

Název nakladatele

JMLR

Místo vydání

Cambridge

Místo konání akce

Barcelona

Datum konání akce

9. 12. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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