Ake (version 1.0.2)

hcvc.fun: Cross-validation function for bandwidth selection for continuous data

Description

The (S3) generic function hcvc.fun computes the cross-validation bandwidth selector.

Usage

hcvc.fun(Vec,...)
# S3 method for default
hcvc.fun(Vec, bw = NULL, type_data, ker, a0 = 0, a1 = 1, ...)

Value

Returns a list containing:

hcv

value of bandwidth parameter.

CV

the values of cross-validation function.

seq_h

the sequence of bandwidths where the cross validation is computed.

Arguments

Vec

The data sample from which the estimate is to be computed.

bw

The sequence of bandwidths where to compute the cross-validation. Default value is NULL.

type_data

The sample data type.

ker

The associated kernel.

a0

The left bound of the extended beta. Default value is 0.

a1

The right bound of the extended beta.Default value is 1.

...

Further arguments.

Author

W. E. Wansouwé, S. M. Somé and C. C. Kokonendji

Details

hcvc.fun implements the choice of the bandwidth \(h\) using the cross-validation approach of a kernel density estimator.

References

Chen, S. X. (1999). Beta kernels estimators for density functions, Computational Statistics and Data Analysis 31, 131 - 145.

Chen, S. X. (2000). Gamma kernels estimators for density functions, Annals of the Institute of Statistical Mathematics 52, 471 - 480.

Libengué, F.G. (2013). Méthode Non-Paramétrique par Noyaux Associés Mixtes et Applications, Ph.D. Thesis Manuscript (in French) to Université de Franche-Comté, Besançon, France and Université de Ouagadougou, Burkina Faso, June 2013, LMB no. 14334, Besançon.

Igarashi, G. and Kakizawa, Y. (2015). Bias correction for some asymmetric kernel estimators, Journal of Statistical Planning and Inference 159, 37 - 63.

Examples

V=rgamma(100,1.5,2.6)
if (FALSE) {
hcvc.fun(V,NULL,"continuous","GA")
}