Detecting Complete and Joint Mixability

Journal of Computational and Applied Mathematics, 280, 174–187

19 Pages Posted: 7 Aug 2014 Last revised: 2 Jun 2015

See all articles by Giovanni Puccetti

Giovanni Puccetti

University of Milan - Department of Economics, Management and Quantitative Methods (DEMM)

Ruodu Wang

University of Waterloo - Department of Statistics and Actuarial Science

Date Written: 2014

Abstract

We introduce the Mixability Detection Procedure (MDP) to check whether a set of d distribution 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.

Keywords: Joint mixability, Complete mixability, Degree of mixability, Variance reduction, Rearrangement algorithm.

JEL Classification: [AMS2010] 60E05, 65C50, 65C60, 62E17

Suggested Citation

Puccetti, Giovanni and Wang, Ruodu, Detecting Complete and Joint Mixability (2014). Journal of Computational and Applied Mathematics, 280, 174–187, Available at SSRN: https://ssrn.com/abstract=2476802 or http://dx.doi.org/10.2139/ssrn.2476802

Giovanni Puccetti

University of Milan - Department of Economics, Management and Quantitative Methods (DEMM) ( email )

Via Conservatorio, 7
Milan, 20122
Italy

Ruodu Wang (Contact Author)

University of Waterloo - Department of Statistics and Actuarial Science ( email )

Waterloo, Ontario N2L 3G1
Canada

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