Date and Time: January 16th, 2018, 10:00 - 11:30 am
Room: A 101 in the Economics Building (Museum)
By a theorem due to Sklar in 1959, a multivariate distribution can be represented in terms of its underlying margins by binding them together a copula function. Copulas are useful devices to explain the dependence structure between variables by eliminating the influence of marginals.
A copula method for understanding multivariate distributions has a relatively short history in statistics literature; most of the statistical applications have arisen in the last twenty years. In this talk, diverse approaches to directional dependence via copula will be introduced with real examples using financial data, and psychology data. In addition, I introduce quality control charts by using copula conditional distributions.
About the Speaker
Prof. Dr. Jong-Min Kim is professor of statistics at the University of Minnesota-Morris. His research interests are statistical genetics, sample survey methods and cluster analysis.