CIRCUIT BREAKER DATA ANALYSIS USING COPULA CORRELATION

A copula is a function that joins multivariate distribution functions to their margins (i.e. marginal distribution functions), Nelsen (2006). Copulas are widely used in finance and economics for time series analysis, Zifeng et al (2018), and approaches based on them have found application in engineering as well, typically in civil and reliability engineering. As well known, the copula captures the information about the correlation structure between random variables, however, it contains no information on their respective marginal distributions because the copula margins are uniform. This fundamental property makes copulas a particularly useful set of tools because they allow to separate the marginal distributions of random variables from their joint distribution, study of complex dependence and correlation and model extreme events dependence. In the paper, starting from the experience reported in Alice et al (2019) two applications based on the data extracted by a dataset provided by ABB will be proposed.