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On Representations of Divergence Measures and Related Quantities in Exponential Families
| Content Provider | MDPI |
|---|---|
| Author | Bedbur, Stefan Kamps, Udo |
| Copyright Year | 2021 |
| Description | Within exponential families, which may consist of multi-parameter and multivariate distributions, a variety of divergence measures, such as the Kullback–Leibler divergence, the Cressie–Read divergence, the Rényi divergence, and the Hellinger metric, can be explicitly expressed in terms of the respective cumulant function and mean value function. Moreover, the same applies to related entropy and affinity measures. We compile representations scattered in the literature and present a unified approach to the derivation in exponential families. As a statistical application, we highlight their use in the construction of confidence regions in a multi-sample setup. |
| Starting Page | 726 |
| e-ISSN | 10994300 |
| DOI | 10.3390/e23060726 |
| Journal | Entropy |
| Issue Number | 6 |
| Volume Number | 23 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-06-08 |
| Access Restriction | Open |
| Subject Keyword | Entropy Statistics and Probability Exponential Family Cumulant Function Mean Value Function Divergence Measure Distance Measure Affinity |
| Content Type | Text |
| Resource Type | Article |
