mkde.tune: Tuning of the bandwidth h of the kernel using the maximum...

In Compositional: Compositional Data Analysis

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) )

Compositional documentation built on Oct. 9, 2024, 5:10 p.m.