Parameter estimation of nonlinear econometric models using particle swarm optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F10%3A86076677" target="_blank" >RIV/61989100:27510/10:86076677 - 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

Parameter estimation of nonlinear econometric models using particle swarm optimization

Popis výsledku v původním jazyce

Global optimization is an essential component of econometric modeling. Optimization in econometrics is often difficult due to irregular cost functions characterized by multiple local optima. The goal of this paper is to apply a relatively new stochasticglobal technique, particle swarm optimization, to the well-known but difficult disequilibrium problem. Because of its co-operative nature and balance of local and global search, particle swarm is successful in optimizing the disequilibrium maximum likelihood function, providing better values than those reported in the literature obtained using other stochastic techniques. These encouraging results suggest that particle swarm optimization may be successfully applied to difficult econometrics problems, possibly in conjunction with existing methods.

Název v anglickém jazyce

Parameter estimation of nonlinear econometric models using particle swarm optimization

Popis výsledku anglicky

Global optimization is an essential component of econometric modeling. Optimization in econometrics is often difficult due to irregular cost functions characterized by multiple local optima. The goal of this paper is to apply a relatively new stochasticglobal technique, particle swarm optimization, to the well-known but difficult disequilibrium problem. Because of its co-operative nature and balance of local and global search, particle swarm is successful in optimizing the disequilibrium maximum likelihood function, providing better values than those reported in the literature obtained using other stochastic techniques. These encouraging results suggest that particle swarm optimization may be successfully applied to difficult econometrics problems, possibly in conjunction with existing methods.

Druh

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

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název periodika

Ekonomická revue - Central European Review of Economics Issues

ISSN

1212-3951

e-ISSN

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Svazek periodika

13

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

7

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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