Compositional (version 1.5)

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

Value

A list including:

hopt

The optimal bandwidth value.

maximum

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

Details

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

References

Arsalane Chouaib Guidoum (2015). Kernel Estimator and Bandwidth Selection for Density and its Derivatives. The kedd 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(iris[, 1:4], c(0.1, 3) )