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SIGMA 20 (2024), 094, 22 pages arXiv:2402.08663
https://doi.org/10.3842/SIGMA.2024.094
Contribution to the Special Issue on Asymptotics and Applications of Special Functions in Memory of Richard Paris
Complete Asymptotic Expansions for the Normalizing Constants of High-Dimensional Matrix Bingham and Matrix Langevin Distributions
Armine Bagyan and Donald Richards
Department of Statistics, Pennsylvania State University, University Park, PA 16802, USA
Received February 28, 2024, in final form October 10, 2024; Published online October 21, 2024
Abstract
For positive integers $d$ and $p$ such that $d \ge p$, let $\mathbb{R}^{d \times p}$ denote the set of $d \times p$
real matrices, $I_p$ be the identity matrix of order $p$, and $V_{d,p} = \bigl\{x \in \mathbb{R}^{d \times p} \mid x'x = I_p\bigr\}$
be the Stiefel manifold in $\mathbb{R}^{d \times p}$. Complete asymptotic expansions as $d \to \infty$ are obtained for the
normalizing constants of the matrix Bingham and matrix Langevin probability distributions on $V_{d,p}$. The accuracy
of each truncated expansion is strictly increasing in $d$; also, for sufficiently large $d$, the accuracy is strictly increasing in $m$,
the number of terms in the truncated expansion. Lower bounds are obtained for the truncated expansions when the matrix
parameters of the matrix Bingham distribution are positive definite and when the matrix parameter of the matrix Langevin
distribution is of full rank. These results are applied to obtain the rates of convergence of the asymptotic expansions as both
$d \to \infty$ and $p \to \infty$. Values of $d$ and $p$ arising in numerous data sets are used to illustrate the rate of convergence
of the truncated approximations as $d$ or $m$ increases. These results extend recently-obtained asymptotic expansions for
the normalizing constants of the high-dimensional Bingham distributions.
Key words: Frobenius norm; generalized hypergeometric function of matrix argument; Grassmann manifold; Hadamard's inequality; hippocampus; neural spike activity; Stiefel manifold; Super Chris (the rat); symmetric cone; zonal polynomial.
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References
- Bagyan A., Richards D., Complete asymptotic expansions and the high-dimensional Bingham distributions, TEST 33 (2024), 540-563, arXiv:2303.04575.
- Bingham C., An antipodally symmetric distribution on the sphere, Ann. Statist. 2 (1974), 1201-1225.
- Bingham C., Chang T., Richards D., Approximating the matrix Fisher and Bingham distributions: applications to spherical regression and Procrustes analysis, J. Multivariate Anal. 41 (1992), 314-337.
- Chikuse Y., Statistics on special manifolds, Lect. Notes Stat., Vol. 174, Springer, New York, 2003.
- de Waal D.J., On the normalizing constant for the Bingham-von Mises-Fisher matrix distribution, South African Statist. J. 13 (1979), 103-112.
- Ding H., Gross K.I., Richards D.St.P., Ramanujan's master theorem for symmetric cones, Pacific J. Math. 175 (1996), 447-490.
- Dryden I.L., Statistical analysis on high-dimensional spheres and shape spaces, Ann. Statist. 33 (2005), 1643-1665, arXiv:math/0508279.
- Edelman A., Kostlan E., Shub M., How many eigenvalues of a random matrix are real?, J. Amer. Math. Soc. 7 (1994), 247-267.
- Faraut J., Korányi A., Analysis on symmetric cones, Oxford Math. Monogr., The Clarendon Press, Oxford University Press, New York, 1994.
- Granados-Garcia G., Fiecas M., Babak S., Fortin N.J., Ombao H., Brain waves analysis via a non-parametric Bayesian mixture of autoregressive kernels, Comput. Statist. Data Anal. 174 (2022), 107409, 181 pages, arXiv:2102.11971.
- Gross K.I., Richards D.St.P., Special functions of matrix argument. I. Algebraic induction, zonal polynomials, and hypergeometric functions, Trans. Amer. Math. Soc. 301 (1987), 781-811.
- Hoff P.D., Simulation of the matrix Bingham-von Mises-Fisher distribution, with applications to multivariate and relational data, J. Comput. Graph. Statist. 18 (2009), 438-456, arXiv:0712.4166.
- Holbrook A., Vandenberg-Rodes A., Shahbaba B., Bayesian inference on matrix manifolds for linear dimensionality reduction, arXiv:1606.04478.
- Horn R.A., Johnson C.R., Matrix analysis, 2nd ed., Cambridge University Press, Cambridge, 2012.
- Impens C., Stirling's series made easy, Amer. Math. Monthly 110 (2003), 730-735.
- James A.T., Distributions of matrix variates and latent roots derived from normal samples, Ann. Math. Statist. 35 (1964), 475-501.
- James A.T., Calculation of zonal polynomial coefficients by use of the Laplace-Beltrami operator, Ann. Math. Statist. 39 (1968), 1711-1718.
- James A.T., The variance information manifold and the functions on it, in Multivariate Analysis III, Academic Press, New York, 1973, 157-169.
- Jauch M., Hoff P.D., Dunson D.B., Monte Carlo simulation on the Stiefel manifold via polar expansion, J. Comput. Graph. Statist. 30 (2021), 622-631, arXiv:1906.07684.
- Jiu L., Koutschan C., Calculation and properties of zonal polynomials, Math. Comput. Sci. 14 (2020), 623-640, arXiv:2001.11599.
- Jupp P.E., Mardia K.V., Maximum likelihood estimators for the matrix von Mises-Fisher and Bingham distributions, Ann. Statist. 7 (1979), 599-606.
- Jupp P.E., Mardia K.V., A unified view of the theory of directional statistics, 1975-1988, Int. Stat. Rev. 57 (1989), 261-294.
- Khatri C.G., Mardia K.V., The von Mises-Fisher matrix distribution in orientation statistics, J. Roy. Statist. Soc. Ser. B 39 (1977), 95-106.
- Kume A., Preston S.P., Wood A.T.A., Saddlepoint approximations for the normalizing constant of Fisher-Bingham distributions on products of spheres and Stiefel manifolds, Biometrika 100 (2013), 971-984.
- Kume A., Wood A.T.A., Saddlepoint approximations for the Bingham and Fisher-Bingham normalising constants, Biometrika 92 (2005), 465-476.
- Kushner H.B., On the expansion of $C^*_\rho(V+I)$ as a sum of zonal polynomials, J. Multivariate Anal. 17 (1985), 84-98.
- Ledermann W., Introduction to group characters, Cambridge University Press, Cambridge, 1977.
- Mantoux C., Couvy-Duchesne B., Cacciamani F., Epelbaum S., Durrleman S., Allassonnière S., Understanding the variability in graph data sets through statistical modeling on the Stiefel manifold, Entropy 23 (2021), 490, 34 pages.
- Mardia K.V., Jupp P.E., Directional statistics, Wiley Ser. Probab. Stat., John Wiley & Sons, Chichester, 1999.
- Muirhead R.J., Aspects of multivariate statistical theory, Wiley Ser. Probab. Math. Stat., John Wiley & Sons, New York, 1982, .
- Oualkacha K., Rivest L.P., On the estimation of an average rigid body motion, Biometrika 99 (2012), 585-598.
- Parkhurst A.M., James A.T., Zonal polynomials of order 1 through 12, in Selected Tables in Mathematical Statistics, Vol. II, American Mathematical Society, Providence, RI, 1974, 199-388.
- Prentice M.J., Antipodally symmetric distributions for orientation statistics, J. Statist. Plann. Inference 6 (1982), 205-214.
- Richards D.St.P., Applications of invariant differential operators to multivariate distribution theory, SIAM J. Appl. Math. 45 (1985), 280-288.
- Richards D.St.P., Functions of matrix argument, in NIST Handbook of Mathematical Functions, Vol. 35, U.S. Department of Commerce, National Institute of Standards and Technology, Washington, DC, 2010, 767-774.
- Sudlow C., Gallacher J., Allen N., Beral V., Burton P., Danesh J., Downey P., Elliott P., Green J., Landray M., UK Biobank: An open access resource for identifying the causes of a wide range of complex diseases of middle and old age, PLoS Med. 12 (2015), e1001779, 11 pages.
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