Saddlepoint approximations for the normalizing constant of Fisher--Bingham distributions on products of spheres and Stiefel manifolds
In an earlier paper Kume & Wood (2005) showed how the normalizing constant of the Fisher--Bingham distribution on a sphere can be approximated with high accuracy using a univariate saddlepoint density approximation. In this sequel, we extend the approach to a more general setting and derive saddlepoint approximations for the normalizing constants of multicomponent Fisher--Bingham distributions on Cartesian products of spheres, and Fisher--Bingham distributions on Stiefel manifolds. In each case, the approximation for the normalizing constant is essentially a multivariate saddlepoint density approximation for the joint distribution of a set of quadratic forms in normal variables. Both first-order and second-order saddlepoint approximations are considered. Computational algorithms, numerical results and theoretical properties of the approximations are presented. In the challenging high-dimensional settings considered in this paper the saddlepoint approximations perform very well in all examples considered. Copyright 2013, Oxford University Press.
Year of publication: |
2013
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Authors: | Kume, A. ; Preston, S. P. ; Wood, Andrew T. A. |
Published in: |
Biometrika. - Biometrika Trust, ISSN 0006-3444. - Vol. 100.2013, 4, p. 971-984
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Publisher: |
Biometrika Trust |
Saved in:
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