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Copula Functions and Applications in Engineering

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Logistics, Supply Chain and Financial Predictive Analytics

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Abstract

Copula functions also known as copulas, which connect the marginal distributions to their joint distributions, are useful in simulating the linear or nonlinear relationships among multivariate data in the scientific and engineering studies. Copula is a multivariate distribution function with marginally uniform random variables on [0, 1]. Copula functions have some appealing properties such as they allow scale-free measures of dependence and are useful in constructing families of joint distributions. As seen recently, copulas have been applied in statistics, insurance, finance, economics, survival analysis, image processing, and engineering applications. In this paper, we aim to briefly describe the copula functions, their properties, copula families, simulations, and examples of copula applications.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Northern British Columbia, Prince George, Canada

    Pranesh Kumar

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  1. Pranesh Kumar
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Correspondence to Pranesh Kumar .

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Editors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Madhu Jain

  3. Kent Business School, Centre for Logistics and Heuristic Optimization (CLHO), University of Kent, Canterbury, Kent, United Kingdom

    Said Salhi

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Kumar, P. (2019). Copula Functions and Applications in Engineering. In: Deep, K., Jain, M., Salhi, S. (eds) Logistics, Supply Chain and Financial Predictive Analytics. Asset Analytics. Springer, Singapore. https://doi.org/10.1007/978-981-13-0872-7_15

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