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 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.