In this paper we show how one canimplement in practice the bandwidth selection in deconvolution recursive kernel estimators of a probability density function defined by the stochastic approximation ...
Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...
SIAM Journal on Numerical Analysis, Vol. 56, No. 1 (2018), pp. 274-295 (22 pages) In this paper, a numerical solution of partial differential equations on the unit sphere is given by using a kernel ...
This optimal value is unknown, and so approximations methods are required. For a derivation and discussion of these results, refer to Silverman (1986, Chapter 3) and Jones, Marron, and Sheather (1996) ...
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