On choosing and bounding probability metrics

被引:733
作者
Gibbs, AL
Su, FE
机构
[1] York Univ, Dept Math & Stat, N York, ON M3J 1P3, Canada
[2] Harvey Mudd Coll, Dept Math, Claremont, CA 91711 USA
关键词
discrepancy; hellinger distance; probability metrics; prokhorov metric; relative entropy; rates of convergence; wasserstein distance;
D O I
10.2307/1403865
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
When studying convergence of measures, an. important, issue is the choice of probability metric. We provide a summary and some new results concerning bounds among some important probability metrics/distances that are used by statisticians and probabilists. Knowledge of other metrics can provide a means of deriving bounds for another one in an applied problem. Considering other metrics can also provide alternate insights. We also give examples that show that rates of convergence can strongly depend on the metric chosen. Careful consideration is necessary when choosing a metric.
引用
收藏
页码:419 / 435
页数:17
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