Tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data
Tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data whit cross validation.
vmfkde.tune(x, low = 0.1, up = 1)
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. |
Fast tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data via cross validation.
A vector including two elements:
Optimal h |
The best H found. |
cv |
The value of the maximised pseudo-likelihood. |
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>
Garcia Portugues 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.
x <- rvmf(100, rnorm(3), 15) vmfkde.tune(x)
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