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Directional (version 6.8)

Tuning of the bandwidth parameter in the von Mises-Fisher kernel: Tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data

Description

Tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data whit cross validation.

Usage

vmfkde.tune(x, low = 0.1, up = 1)

Value

A vector including two elements:

Optimal h

The best H found.

cv

The value of the maximised pseudo-likelihood.

Arguments

x

A matrix with the data in Euclidean cordinates, i.e. unit vectors.

low

The lower value of the bandwdith to search.

up

The upper value of the bandwdith to search.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>.

Details

Fast tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data via cross validation.

References

Garcia P.E. (2013). Exact risk improvement of bandwidth selectors for kernel density estimation with directional data. Electronic Journal of Statistics, 7, 1655--1685.

Wand M.P. and Jones M.C. (1994). Kernel smoothing. Crc Press.

See Also

vmf.kde,vmf.kerncontour, vm.kde, vmkde.tune

Examples

Run this code
x <- rvmf(100, rnorm(3), 15)
vmfkde.tune(x)

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