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http://hdl.handle.net/1942/9517
Title: | Flexible modeling based on copulas in nonparametric median regression |
Authors: | BRAEKERS, Roel VAN KEILEGOM, Ingrid |
Issue Date: | 2009 |
Publisher: | Elsevier Inc. |
Source: | JOURNAL OF MULTIVARIATE ANALYSIS, 100(6). p. 1270-1281 |
Abstract: | Consider the model Y=m(X)+ε, where m()=med(Y|) is unknown but smooth. It is often assumed that ε and X are independent. However, in practice this assumption is violated in many cases. In this paper we propose modeling the dependence between ε and X by means of a copula model, i.e. , where is a copula function depending on an unknown parameter θ, and Fε and FX are the marginals of ε and X. Since many parametric copula families contain the independent copula as a special case, the so-obtained regression model is more flexible than the ‘classical’ regression model. We estimate the parameter θ via a pseudo-likelihood method and prove the asymptotic normality of the estimator, based on delicate empirical process theory. We also study the estimation of the conditional distribution of Y given X. The procedure is illustrated by means of a simulation study, and the method is applied to data on food expenditures in households. |
Keywords: | Conditional distribution; Copulas; Empirical processes; Median regression; Nonparametric regression; Quantiles; Weak convergence |
Document URI: | http://hdl.handle.net/1942/9517 |
ISSN: | 0047-259X |
DOI: | 10.1016/j.jmva.2008.11.009 |
ISI #: | 000265805600014 |
Category: | A1 |
Type: | Journal Contribution |
Validations: | ecoom 2010 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Flexible modeling based on copulas.pdf | Peer-reviewed author version | 629.54 kB | Adobe PDF | View/Open |
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