Journal ArticleDOI
Appell's hypergeometric functions of matrix arguments
Daya K. Nagar,Saralees Nadarajah +1 more
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Appell's hypergeometric functions F1, F2 and F3 of matrix arguments are defined and their properties are studied in this article, where applications to distribution theory are described in a technical report.Abstract:
Appell's hypergeometric functions F1, F2 and F3 of matrix arguments are defined and their properties are studied. Applications to distribution theory are described in a technical report due to the authors.read more
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Optimal Bayesian Transfer Learning
TL;DR: A joint Wishart distribution for the precision matrices of the Gaussian feature-label distributions in the source and target domains to act like a bridge that transfers the useful information of the source domain to help classification in the target domain by improving the target posteriors is defined.
Journal ArticleDOI
On the hypergeometric matrix functions of two variables
Ravi Dwivedi,Vivek Sahai +1 more
TL;DR: In this article, the generalized hypergeometric function with matrix parameters was introduced and two variable Appell matrix functions were defined and their regions of convergence as well as integral representations were found.
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References
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Book
Aspects of multivariate statistical theory
TL;DR: In this paper, the authors present a set of standard tests on Covariance Matrices and Mean Vectors, and test independence between k Sets of Variables and Canonical Correlation Analysis.
Book
Generalized hypergeometric functions
TL;DR: The Generalized Gauss Function (GGF) as mentioned in this paper is a generalized version of the Gauss function that can be used to compute the generalized Gauss functions (GFG).
Book
Generalized Hypergeometric Series
TL;DR: Koornwinder as discussed by the authors gave identitity (2.5) with N = 0 and formulas (5.3), 5.3, and 5.4) substituted.
Journal ArticleDOI
Distributions of Matrix Variates and Latent Roots Derived from Normal Samples
TL;DR: In this article, the authors defined the hypergeometric functions $_pF_q$ of matrix argument which occur in the multivariate distributions are defined by their expansions in zonal polynomials as defined in Section 5.
Journal ArticleDOI
Matrix Variate Distributions
TL;DR: In this article, Matrix Variate Distributions (MVD) are used to measure the degree of similarity between distributions in a set of distributions, i.e., matrix variance distributions.
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