Abstract Details
Activity Number:
|
465
|
Type:
|
Contributed
|
Date/Time:
|
Wednesday, August 6, 2014 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Statistical Graphics
|
Abstract #312906
|
View Presentation
|
Title:
|
Modeling Directional Dependence: A Copula Approach
|
Author(s):
|
Engin Sungur*+ and Jessica Orth
|
Companies:
|
University of Minnesota and University of Iowa
|
Keywords:
|
Copulas ;
Dependence Plots ;
Directional dependence ;
Jacobi rotations ;
Angular correlation plots
|
Abstract:
|
Understanding and modeling multivariate dependence structures depending upon the direction are challenging but an interest of theoretical and applied researchers. Directional dependence modeling is an effective approach on answering many research questions in various areas such as economics, finance, biostatistics, and bioinformatics. We formally define the directional dependence and introduce a parameterization through rotation angles to model it. A new class of copulas with directional dependence property has been constructed by using oblique Jacobi rotation of a Gaussian and uniform random vectors. The properties of this family are presented and possible applications are given. Also, a systematic approach to generate p-dimensional copulas under various directional dependence settings is introduced. This construction allows us to model and measure directional dependence in a meaningful way and leads to informative graphical displays.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.