Automatické modelování a SV učící stroj s aplikací na modelování inflace

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F05%3A%230000179" target="_blank" >RIV/47813059:19240/05:#0000179 - 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

Automated Modelling and an SV Machine Applied to Inflation Modelling

Popis výsledku v původním jazyce

In Support Vector Machines (SVM´s), a non-linear model is estimated based on solving a Quadratic Programming (QP) problem. Dynamic and SVM´s modelling approaches are used for automated specification of a functional form of the model. Based on dynamic modelling, we provide the fit of inflation models in the Slovak Republic and use them as a tool to compare their forecasting abilities with those obtained using SVM´s method. Some methodological contributions are made to dynamic and SVM´s modelling approaches in economics and to their use in data mining systems. The article discusses building a structural model by modelling strategy described as being a "specific to general" methodology. The study discusses, analytically and numerically demonstrates the quality and interpretability of the obtained results. The SVM´s methodology is extended to predict the time series models. In conclusion the article refers to the knowledge about data mining written by Ken Holden.

Název v anglickém jazyce

Automated Modelling and an SV Machine Applied to Inflation Modelling

Popis výsledku anglicky

In Support Vector Machines (SVM´s), a non-linear model is estimated based on solving a Quadratic Programming (QP) problem. Dynamic and SVM´s modelling approaches are used for automated specification of a functional form of the model. Based on dynamic modelling, we provide the fit of inflation models in the Slovak Republic and use them as a tool to compare their forecasting abilities with those obtained using SVM´s method. Some methodological contributions are made to dynamic and SVM´s modelling approaches in economics and to their use in data mining systems. The article discusses building a structural model by modelling strategy described as being a "specific to general" methodology. The study discusses, analytically and numerically demonstrates the quality and interpretability of the obtained results. The SVM´s methodology is extended to predict the time series models. In conclusion the article refers to the knowledge about data mining written by Ken Holden.

Druh

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

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

<a href="/cs/project/GA402%2F05%2F2768" target="_blank" >GA402/05/2768: Pokročilé statistické a ekonometrické techniky pro modelování a predikci ekonomických časových řad</a><br>

Návaznosti

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

Rok uplatnění

2005

Kód důvěrnosti údajů

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

Název periodika

ECON 05 /selected research papers/

ISSN

0862-7908

e-ISSN

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Svazek periodika

neuvdeno

Číslo periodika v rámci svazku

2005

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

13

Strana od-do

214-226

Kód UT WoS článku

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EID výsledku v databázi Scopus

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