KDE_ICV: Computing the kernel density estimate based on the ICV...

In osavchuk/ICV: Indirect cross-validation (ICV) for kernel density estimation

Description

Computing the Gaussian density estimate based on h_ICV.

Usage

KDE_ICV(x)

Arguments

x	numerical vector of data.

Details

Computing the Gaussian density estimate based on h_ICV. The ICV selection kernel L_ICV is based on (α,σ)=(2.42,5.06).

Value

A list containing the following components:

arg

vector of sorted values of the argument at which the density estmate is computed,

y

vector of density estimates at the corresponding values of the argument.

The function also produces a graph of the resulting ICV kernel density estimate.

References

• Savchuk, O.Y., Hart, J.D., Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the American Statistical Association, 105(489), 415-423.

• Savchuk, O.Y., Hart, J.D., Sheather, S.J. (2009). An empirical study of indirect cross-validation. Nonparametric Statistics and Mixture Models: A Festschrift in Honor of Thomas P. Hettmansperger. World Scientific Publishing, 288-308.

See Also

ICV, h_ICV, L_ICV, LocICV, C_ICV.

Examples

#Example (Density estimate for eruption duration of the Old Faithful Geyser).
data=faithful[[1]]
dens=KDE_ICV(data)

osavchuk/ICV documentation built on May 24, 2019, 3:59 p.m.