Distance correlation coefficients for Lancaster distributions
We consider the problem of calculating distance correlation coefficients between random vectors whose joint distributions belong to the class of Lancaster distributions. We derive under mild convergence conditions a general series representation for the distance covariance for these distributions. T...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article (Journal) |
| Language: | English |
| Published: |
February 2017
|
| In: |
Journal of multivariate analysis
Year: 2016, Volume: 154, Pages: 19-39 |
| ISSN: | 1095-7243 |
| DOI: | 10.1016/j.jmva.2016.10.012 |
| Online Access: | Verlag, Volltext: http://dx.doi.org/10.1016/j.jmva.2016.10.012 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0047259X16301245 
|
| Author Notes: | Johannes Dueck, Dominic Edelmann, and Donald Richards |
| Summary: | We consider the problem of calculating distance correlation coefficients between random vectors whose joint distributions belong to the class of Lancaster distributions. We derive under mild convergence conditions a general series representation for the distance covariance for these distributions. To illustrate the general theory, we apply the series representation to derive explicit expressions for the distance covariance and distance correlation coefficients for the bivariate normal distribution and its generalizations of Lancaster type, the multivariate normal distributions, and the bivariate gamma, Poisson, and negative binomial distributions which are of Lancaster type. |
|---|---|
| Item Description: | Available online 31 October 2016 Gesehen am 24.05.2018 |
| Physical Description: | Online Resource |
| ISSN: | 1095-7243 |
| DOI: | 10.1016/j.jmva.2016.10.012 |