| kfun {evmix} | R Documentation | 
Various subsidiary kernel function, conversion of bandwidths and evaluating certain kernel integrals.
Description
Functions for checking the inputs to the kernel functions, evaluating 
integrals \int u^l K*(u) du for l = 0, 1, 2 and conversion between the two bandwidth
definitions.
Usage
check.kinputs(x, lambda, bw, kerncentres, allownull = FALSE)
check.kernel(kernel)
check.kbw(lambda, bw, allownull = FALSE)
klambda(bw = NULL, kernel = "gaussian", lambda = NULL)
kbw(lambda = NULL, kernel = "gaussian", bw = NULL)
ka0(truncpoint, kernel = "gaussian")
ka1(truncpoint, kernel = "gaussian")
ka2(truncpoint, kernel = "gaussian")
Arguments
x | 
 location to evaluate KDE (single scalar or vector)  | 
lambda | 
 bandwidth for kernel (as half-width of kernel) or   | 
bw | 
 bandwidth for kernel (as standard deviations of kernel) or   | 
kerncentres | 
 kernel centres (typically sample data vector or scalar)  | 
allownull | 
 logical, where TRUE permits NULL values  | 
kernel | 
 kernel name (  | 
truncpoint | 
 upper endpoint as standardised location   | 
Details
Various boundary correction methods require integral of (partial moments of)
kernel within the range of support, over the range [-1, p] where p
is the truncpoint determined by the standardised distance of location x
where KDE is being evaluated to the lower bound of zero, i.e. truncpoint = x/lambda.
The exception is the normal kernel which has unbounded support so the [-5*\lambda, p] where
lambda is the standard deviation bandwidth. There is a function for each partial moment
of degree (0, 1, 2):
-  
ka0-\int_{-1}^{p} K*(z) dz -  
ka1-\int_{-1}^{p} u K*(z) dz -  
ka2-\int_{-1}^{p} u^2 K*(z) dz 
Notice that when evaluated at the upper endpoint on the support p = 1
(or p = \infty for normal) these are the zeroth, first and second moments. In the
normal distribution case the lower bound on the region of integration is \infty but
implemented here as -5*\lambda. 
These integrals are all specified in closed form, there is no need for numerical integration
(except normal which uses the pnorm function). 
See kpu for list of kernels and discussion of bandwidth 
definitions (and their default values):
-  
bw- in terms of number of standard deviations of the kernel, consistent with the defined values in thedensityfunction in theRbase libraries -  
lambda- in terms of half-width of kernel 
The klambda function converts the bw to the lambda
equivalent, and kbw applies converse. These conversions are
kernel specific as they depend on the kernel standard deviations. If both bw and
lambda are provided then the latter is used by default. If neither are provided 
(bw=NULL and lambda=NULL) then default is lambda=1.
check.kinputs checks all the kernel function inputs,
check.klambda checks the pair of inputted bandwidths and
check.kernel checks the kernel names.
Value
klambda and kbw return the
lambda and bw bandwidths respectively.
The checking functions check.kinputs,
check.klambda and check.kernel
will stop on errors and return no value.
ka0, ka1 and ka2
return the partial moment integrals specified above.
Author(s)
Carl Scarrott carl.scarrott@canterbury.ac.nz.
References
http://en.wikipedia.org/wiki/Kernel_density_estimation
http://en.wikipedia.org/wiki/Kernel_(statistics)
Wand and Jones (1995). Kernel Smoothing. Chapman & Hall.
See Also
kernels, density, 
kden and bckden.
Other kernels: kernels
Examples
xx = seq(-2, 2, 0.01)
plot(xx, kdgaussian(xx), type = "l", col = "black",ylim = c(0, 1.2))
lines(xx, kduniform(xx), col = "grey")
lines(xx, kdtriangular(xx), col = "blue")
lines(xx, kdepanechnikov(xx), col = "darkgreen")
lines(xx, kdbiweight(xx), col = "red")
lines(xx, kdtriweight(xx), col = "purple")
lines(xx, kdtricube(xx), col = "orange")
lines(xx, kdparzen(xx), col = "salmon")
lines(xx, kdcosine(xx), col = "cyan")
lines(xx, kdoptcosine(xx), col = "goldenrod")
legend("topright", c("Gaussian", "uniform", "triangular", "Epanechnikov",
"biweight", "triweight", "tricube", "Parzen", "cosine", "optcosine"), lty = 1,
col = c("black", "grey", "blue", "darkgreen", "red", "purple",
  "salmon", "orange", "cyan", "goldenrod"))