Some theoretical results on tensor elliptical distribution

2017/09/04 by ‎M‎ohammad Arashi, Arashi, M. · 1 citation
Mathematics · Medicine · #15A69 #60E10 Secondary: 53A45 #Advanced Neuroimaging Techniques and Applications #FOS: Mathematics #Fractional Differential Equations Solutions #Primary: 62E15 #Statistics Theory (math.ST) #Tensor decomposition and applications

paper · pdf · doi:10.48550/arxiv.1709.00801

openalex publication_date 2017/09/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The multilinear normal distribution is a widely used tool in tensor analysis of magnetic resonance imaging (MRI). Diffusion tensor MRI provides a statistical estimate of a symmetric 2nd-order diffusion tensor, for each voxel within an imaging volume. In this article, tensor elliptical (TE) distribution is introduced as an extension to the multilinear normal (MLN) distribution. Some properties including the characteristic function and distribution of affine transformations are given. An integral representation connecting densities of TE and MLN distributions is exhibited that is used in deriving the expectation of any measurable function of a TE variate.

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• Tensor Elliptical Graphic Model

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