Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation {Compositional}

Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation

Description

Tuning of the bandwidth h of the kernel using the maximum likelihood cross validation.

Usage

mkde.tune( x, low = 0.1, up = 3, s = cov(x) )

Arguments

x

A matrix with Euclidean (continuous) data.

low

The minimum value to search for the optimal bandwidth value.

up

The maximum value to search for the optimal bandwidth value.

s

A covariance matrix. By default it is equal to the covariance matrix of the data, but can change to a robust covariance matrix, MCD for example.

Details

Maximum likelihood cross validation is applied in order to choose the optimal value of the bandwidth parameter. No plot is produced.

Value

A list including:

hopt

The optimal bandwidth value.

maximum

The value of the pseudo-log-likelihood at that given bandwidth value.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail] and Giorgos Athineou <[e-mail]>.

References

Arsalane Chouaib Guidoum (2015). Kernel Estimator and Bandwidth Selection for Density and its Derivatives. The kedd R package. http://cran.r-project.org/web/packages/kedd/vignettes/kedd.pdf

M.P. Wand and M.C. Jones (1995). Kernel smoothing, pages 91-92.

See Also

mkde, comp.kerncontour

Examples

library(MASS)
mkde.tune(as.matrix(iris[, 1:4]), c(0.1, 3) )