Dependence structure analysis of the inverter operational data by means of copula theory

作者：Zagorski Marcin^*; Orkisz Michal

来源：Mechanical Systems and Signal Processing, 2013, 40(2): 439-451.

DOI：10.1016/j.ymssp.2013.06.016

• Copula
• Multivariate distributions
• Tail dependence
• Kendall%26apos
• s tau
• Inverter

The dependence structure between various signals produced by a mechanical system can have in principle a very complex form. In order to reveal statistical information hidden in data, we apply the copula theory, which is a general way of representing dependence structure for multivariate distributions. The proposed framework is demonstrated through a case study of the inverter operational data. Particularly, for the initial analysis of dependencies we use graphical and numerical rank-based methods. Moreover, for the selected pair of signals we estimate parameters of three copula models, and validate the results against the goodness-of-fit test procedure. It is concluded that only one model reflects the dependence structure accordingly and the obtained estimates show correlation with faulty behavior of the system.

• 出版日期2013-11