Semiparametric Regression Estimation in Copula Models

Vilijandas Bagdonavičius; Sergey V. Malov; M. S. Nikulin

doi:10.1080/03610920600637297

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Semiparametric Regression Estimation in Copula Models

Vilijandas Bagdonavičius Sergey V. Malov M. S. Nikulin

Year: 2006 Journal: Communication in Statistics- Theory and Methods Vol: 35 (8)Pages: 1449-1467 Publisher: Taylor & Francis

DOI: 10.1080/03610920600637297

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Abstract

Abstract We consider some methods of semiparametric regression estimation in multivariate models when the common distribution function is represented using a copula and the marginals satisfy a generalized regression model using a transfer functional. Sufficient conditions for consistency and joint asymptotic normality of the finite-dimensional parameters are obtained. Keywords: CopulaGeneralized additive-multiplicative modelMultivariate rank statisticsSemiparametric copulasTransfer functionalMathematics Subject Classification: 62G0562G2062N0262H2062N05

Keywords:

Mathematics Copula (linguistics) Asymptotic distribution Semiparametric regression Multivariate statistics Statistics Consistency (knowledge bases) Semiparametric model Multivariate normal distribution Regression Econometrics Applied mathematics Estimator

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Probability and Risk Models

Social Sciences → Decision Sciences → Management Science and Operations Research

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

Semiparametric Regression Estimation in Copula Models

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