• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.255-269
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• 2004

This paper develops log-density estimation for directional data. The methodology is to use expansions with respect to spherical harmonics followed by estimating the unknown parameters by maximum likelihood. Minimax rates of convergence in terms of the Kullback-Leibler information divergence are obtained.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.153-163
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• 1998

We investigate density estimation problem in the L$^{\infty}$ norm and show that the iii optimal minimax rates are achieved for smooth classes of weakly dependent stationary sequences. Our results are then applied to give uniform convergence rates for various problems including the Gibbs sampler.