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Saddlepoint approximations for the normalizing constant of Fisher--Bingham distributions on products of spheres and Stiefel manifolds

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  • A. Kume
  • S. P. Preston
  • Andrew T. A. Wood

Abstract

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.

Suggested Citation

  • A. Kume & S. P. Preston & Andrew T. A. Wood, 2013. "Saddlepoint approximations for the normalizing constant of Fisher--Bingham distributions on products of spheres and Stiefel manifolds," Biometrika, Biometrika Trust, vol. 100(4), pages 971-984.
  • Handle: RePEc:oup:biomet:v:100:y:2013:i:4:p:971-984
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    File URL: http://hdl.handle.net/10.1093/biomet/ast021
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    Cited by:

    1. Kanti V. Mardia, 2021. "Comments on: Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 59-63, March.

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