Analysis of Income of EU Residents Using Finite Mixtures of Regression Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F16%3A33161733" target="_blank" >RIV/61989592:15310/16:33161733 - isvavai.cz</a>

Výsledek na webu

<a href="http://mme2016.tul.cz/conferenceproceedings/mme2016_conference_proceedings.pdf" target="_blank" >http://mme2016.tul.cz/conferenceproceedings/mme2016_conference_proceedings.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Income of EU Residents Using Finite Mixtures of Regression Models

Popis výsledku v původním jazyce

In situations where the classical linear regression is inapplicable due to a heterogeneity of the population, mixtures of regression models are a popular choice. The method acquires parameters estimates by modelling the mixture conditional distribution of the response given the explanatory variables. The mixture distribution is given by the weighted sum over all components and, in the end, an individual regression models, one for each component, can be estimated simultaneously. The estimation of parameters is done via the expectation-maximization (EM) algorithm, a widely applicable algorithm for computing maximum likelihood estimates from incomplete data. Recently, mixture models are used more and more in various fields, including biology, medicine, genetics and the economics. In this paper, income of residents of EU countries is explored, in further detail we analyse the relationship between an annual old age pension and income of people over 65 years. While the data show evident heterogeneity, the mixture regression approach is required.

Název v anglickém jazyce

Analysis of Income of EU Residents Using Finite Mixtures of Regression Models

Popis výsledku anglicky

In situations where the classical linear regression is inapplicable due to a heterogeneity of the population, mixtures of regression models are a popular choice. The method acquires parameters estimates by modelling the mixture conditional distribution of the response given the explanatory variables. The mixture distribution is given by the weighted sum over all components and, in the end, an individual regression models, one for each component, can be estimated simultaneously. The estimation of parameters is done via the expectation-maximization (EM) algorithm, a widely applicable algorithm for computing maximum likelihood estimates from incomplete data. Recently, mixture models are used more and more in various fields, including biology, medicine, genetics and the economics. In this paper, income of residents of EU countries is explored, in further detail we analyse the relationship between an annual old age pension and income of people over 65 years. While the data show evident heterogeneity, the mixture regression approach is required.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

34th International Conference Mathematical Methods in Economics (MME)

ISBN

978-80-7494-296-9

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

875-880

Název nakladatele

Technická univerzita v Liberci

Místo vydání

Liberec

Místo konání akce

Liberec

Datum konání akce

6. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000385239500150