Kim, Peter T. Deconvolution density estimation on \(\text{SO}(N)\). (English) Zbl 0929.62042 Ann. Stat. 26, No. 3, 1083-1102 (1998). Summary: This paper develops nonparametric deconvolution density estimation over \(SL(N)\), the group of \(N\times N\) orthogonal matrices of determinant 1. The methodology is to use the group and manifold structures to adapt the Euclidean deconvolution techniques to this Lie group environment. This is achieved by employing the theory of group representations explicit to \(SO(N) \). General consistency results are obtained with specific rates of convergence achieved under sufficient smoothness conditions. Application to empirical Bayes prior estimation and inference is also discussed. Cited in 13 Documents MSC: 62G07 Density estimation 22C05 Compact groups 62G05 Nonparametric estimation 20G99 Linear algebraic groups and related topics Keywords:asymptotic variance; asymptotic bias; consistency; differentiable manifold; irreducible representations; unitary matrices × Cite Format Result Cite Review PDF Full Text: DOI References: [1] BAI, Z. D., RAO, C. R. and ZHAO, L. C. 1988. Kernel estimators of density function of directional data. J. Multivariate Anal. 27 24 39. Z. · Zbl 0669.62015 · doi:10.1016/0047-259X(88)90113-3 [2] BERAN, R. 1979. Exponential models for directional data. Ann. Statist. 7 1162 1178. · Zbl 0426.62030 · doi:10.1214/aos/1176344838 [3] BROCKER, T. and TOM DIECK, T. 1985. Representations of Compact Lie Groups. Springer, New Ÿork. Z. [4] CHANG, T. 1986. Spherical regression. Ann. Statist. 14 907 924. Z. · Zbl 0605.62079 · doi:10.1214/aos/1176350041 [5] CHANG, T. 1989. Spherical regression with errors in variables. Ann. Statist. 17 293 306. 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