Electronic Journal of Statistics

Statistical testing of covariate effects in conditional copula models

Elif F. Acar, Radu V. Craiu, and Fang Yao

Full-text: Open access

Abstract

In conditional copula models, the copula parameter is deterministically linked to a covariate via the calibration function. The latter is of central interest for inference and is usually estimated nonparametrically. However, in many applications it is scientifically important to test whether the calibration function is constant or not. Moreover, a correct model of a constant relationship results in significant gains of statistical efficiency. We develop methodology for testing a parametric formulation of the calibration function against a general alternative and propose a generalized likelihood ratio-type test that enables conditional copula model diagnostics. We derive the asymptotic null distribution of the proposed test and study its finite sample performance using simulations. The method is applied to two data examples.

Article information

Source
Electron. J. Statist. Volume 7 (2013), 2822-2850.

Dates
First available in Project Euclid: 2 December 2013

Permanent link to this document
http://projecteuclid.org/euclid.ejs/1385995292

Digital Object Identifier
doi:10.1214/13-EJS866

Mathematical Reviews number (MathSciNet)
MR3148369

Zentralblatt MATH identifier
1280.62052

Subjects
Primary: 62H20: Measures of association (correlation, canonical correlation, etc.)
Secondary: 62G10: Hypothesis testing

Keywords
Constant copula covariate effects dynamic copula local likelihood model diagnostics nonparametric inference

Citation

Acar, Elif F.; Craiu, Radu V.; Yao, Fang. Statistical testing of covariate effects in conditional copula models. Electron. J. Statist. 7 (2013), 2822--2850. doi:10.1214/13-EJS866. http://projecteuclid.org/euclid.ejs/1385995292.


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