2010Electronics LettersRequires access

Copulas of bivariate Rayleigh and log-normal distributions

X. Liu

Open publisher page 6 citations

Abstract

The intrinsic relations between multivariate distributions and their marginal distributions can be clearly characterised by copulas. The bivariate Rayleigh and bivariate log-normal distributions play important roles in both signal processing and digital communications. In this reported work, the formula of bivariate Rayleigh copula is improved and the formula of bivariate log-normal copula is derived. These formulas are in terms of the Marcum Q-function or the Gaussian Q-function, both being supported by Matlab. Thus the copula evaluation process can be expedited both analytically and numerically.

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What this paper is about

The intrinsic relations between multivariate distributions and their marginal distributions can be clearly characterised by copulas. The bivariate Rayleigh and bivariate log-normal distributions play important roles in both signal processing and digital communications. In this reported work, the formula of bivariate Rayleigh copula is improved and the formula of bivariate log-normal copula is derived. These formulas are in terms of the Marcum Q-function or the Gaussian Q-function, both being supported by Matlab. Thus the copula evaluation process can be expedited both analytically and numerically.

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Available abstract

The intrinsic relations between multivariate distributions and their marginal distributions can be clearly characterised by copulas. The bivariate Rayleigh and bivariate log-normal distributions play important roles in both signal processing and digital communications. In this reported work, the formula of bivariate Rayleigh copula is improved and the formula of bivariate log-normal copula is derived. These formulas are in terms of the Marcum Q-function or the Gaussian Q-function, both being supported by Matlab. Thus the copula evaluation process can be expedited both analytically and numerically.

Key concepts: Bivariate analysis, Copula (linguistics), Mathematics, Multivariate normal distribution, Rayleigh scattering, Joint probability distribution, Gaussian, Bivariate data

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