ArticleComputational statistics & data analysis2020
MIXANDMIX: numerical techniques for the computation of empirical spectral distributions of population mixtures.
Article in Computational statistics & data analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- How to reduce dimension with PCA and random projections?IEEE transactions on information theory · 2021Article
- Complex diffusion-weighted image estimation via matrix recovery under general noise models.NeuroImage · 2019Article
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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 nonuniform 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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