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MIXANDMIX: numerical techniques for the computation of empirical spectral distributions of population mixtures

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalCOMPUTATIONAL STATISTICS AND DATA ANALYSIS
Volume141
Early online date28 Jun 2019
DOIs
Accepted/In press21 Jun 2019
E-pub ahead of print28 Jun 2019
PublishedJun 2019

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Abstract

The MIXANDMIX (mixtures by Anderson mixing) tool for the computation of the empirical spectral distribution of random matrices generated by mixtures of populations is described. Within the population mixture model the mapping between the population distributions and the limiting spectral distribution can be obtained by solving a set of systems of non-linear equations, for which an efficient implementation is provided. The contributions include a method for accelerated fixed point convergence, a homotopy continuation strategy to prevent convergence to non-admissible solutions, a blind non-uniform grid construction for effective distribution support detection and approximation, and a parallel computing architecture. Comparisons are performed with available packages for the single population case and with results obtained by simulation for the more general model implemented here. Results show competitive performance and improved flexibility.

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