Coupling for Random Variables
Dmitrii Silvestrov
Additional contact information
Dmitrii Silvestrov: Stockholm University, Department of Mathematics
Chapter Chapter 2 in Coupling and Ergodic Theorems for Semi-Markov-Type Processes I, 2025, pp 51-100 from Springer
Abstract:
Abstract In Chap. 2 , the coupling constructions are described for discrete finite-values random variables, random variables with absolutely continuous distributions, and general random variables taking values in measurable spaces. We give the explicit expressions for maximal coupling probability for random vectors with prescribed marginal distributions of components, the explicit form of the two-dimensional distribution with maximal coupling probability, and stochastic representation for a random vector with maximal coupling probability, as well as give formulas connecting the maximal coupling probability with the variational distance for the corresponding marginal distributions and an explicit formula for this variational distance for absolutely continuous distributions it in terms of the corresponding marginal probability density functions. We also describe the structure of the family of two-dimensional distribution with conditional maximal coupling probability, and give some results concerning the approximation of maximal coupling probability for general and discrete random variables.
Date: 2025
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-89311-7_2
Ordering information: This item can be ordered from
http://www.springer.com/9783031893117
DOI: 10.1007/978-3-031-89311-7_2
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().