Open Journal of Mathematical Analysis
Vol. 5 (2021), Issue 1, pp. 85 – 97
ISSN: 2616-8111 (Online) 2616-8103 (Print)
DOI: 10.30538/psrp-oma2021.0086
ISSN: 2616-8111 (Online) 2616-8103 (Print)
DOI: 10.30538/psrp-oma2021.0086
A study of the power-cosine copula
Christophe Chesneau
Université de Caen Normandie, LMNO, Campus II, Science 3, 14032, Caen, France; christophe.chesneau@gmail.com
Copyright © 2021 Christophe Chesneau. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received: June 9, 2021 – Accepted: June 15, 2021 – Published: June 29, 2021
Abstract
Copulas played a key role in numerous areas of statistics over the last few decades. In this paper, we offer a new kind of trigonometric bivariate copula based on power and cosine functions. We present it via analytical and graphical approaches. We show that it may be used to create a new bivariate normal distribution with interesting shapes. Subsequently, the simplest version of the suggested copula is highlighted. We discuss some of its relationships with the Farlie-Gumbel-Morgensten and simple polynomial-sine copulas, establish that it is a member of a well-known semi-parametric family of copulas, investigate its dependence domains, and show that it has no tail dependence.
Keywords:
Copulas; Farlie-Gumbel-Morgenstern copula; Polynomial-sine copula; Normal distribution; Tail dependence.