We introduce the Mixability Detection Procedure (MDP) to check whether a set of d distri- bution functions is jointly mixable at a given confidence level. The procedure is based on newly established results regarding the convergence rate of the minimal variance problem within the class of joint distribution functions with given marginals. The MDP is able to detect the complete mixability of an arbitrary set of distributions, even in those cases not covered by theoretical results. Stress-tests against borderline cases show that the MDP is fast and reliable.

Detecting complete and joint mixability / Giovanni Puccetti; Ruodu Wang. - In: JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS. - ISSN 1879-1778. - ELETTRONICO. - 280:(2015), pp. 174-187. [10.1016/j.cam.2014.11.050]

Detecting complete and joint mixability

PUCCETTI, GIOVANNI;
2015

Abstract

We introduce the Mixability Detection Procedure (MDP) to check whether a set of d distri- bution functions is jointly mixable at a given confidence level. The procedure is based on newly established results regarding the convergence rate of the minimal variance problem within the class of joint distribution functions with given marginals. The MDP is able to detect the complete mixability of an arbitrary set of distributions, even in those cases not covered by theoretical results. Stress-tests against borderline cases show that the MDP is fast and reliable.
280
174
187
Giovanni Puccetti; Ruodu Wang
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2158/978987
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