The Efficient Evaluation of the Hypergeometric Function of a Matrix Argument
Plamen Koev, Alan Edelman
Abstract
We present new algorithms that efficiently approximate the hypergeometric function of a matrix argument through its expansion as a series of Jack functions. Our algorithms exploit the combinatorial properties of the Jack function, and have complexity that is only linear in the size of the matrix.
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