Mathematics and Statistics Faculty Publications

Title

Estimation and Inference for Dependence in Multivariate Data

Document Type

Article

Abstract

In this paper, a new measure of dependence is proposed. Our approach is based on transforming univariate data to the space where the marginal distributions are normally distributed and then, using the inverse transformation to obtain the distribution function in the original space. The pseudo-maximum likelihood method and the two-stage maximum likelihood approach are used to estimate the unknown parameters. It is shown that the estimated parameters are asymptotical normally distributed in both cases. Inference procedures for testing the independence are also studied.

Publication Date

2010

Publication Title

Journal of Multivariate Analysis

Volume

101

Issue

4

Start Page No.

869

End Page No.

881

ISSN

0047-259X

DOI

10.1016/j.jmva.2009.11.005

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