compKernVals {locpol}R Documentation

Compute kernel values.

Description

Some R code provided to compute kernel related values.

Usage

        computeRK(kernel, lower=dom(kernel)[[1]], upper=dom(kernel)[[2]], 
                        subdivisions = 25)
        computeK4(kernel, lower=dom(kernel)[[1]], upper=dom(kernel)[[2]], 
                        subdivisions = 25)
        computeMu(i, kernel, lower=dom(kernel)[[1]], upper=dom(kernel)[[2]], 
                        subdivisions = 25)
        computeMu0(kernel, lower=dom(kernel)[[1]], upper=dom(kernel)[[2]], 
                        subdivisions = 25)
        Kconvol(kernel,lower=dom(kernel)[[1]],upper=dom(kernel)[[2]],
                        subdivisions = 25)

Arguments

kernel Kernel used to perform the estimation, see Kernels
i Order of kernel moment to compute
lower, upper Integration limits.
subdivisions the maximum number of subintervals.

Details

These functions uses function integrate.

Value

A numeric value returning:

computeK4 The fourth order autoconvolution of K.
computeRK The second order autoconvolution of K.
computeMu0 The integral of K.
computeMu2 The second order moment of K.
computeMu The i-th order moment of K.
Kconvol The autoconvolution of K.

These functions are implemented by means of integrate.

Author(s)

Jorge Luis Ojeda Cabrera.

References

Fan, J. and Gijbels, I. Local polynomial modelling and its applications/. Chapman & Hall, London (1996).

Wand, M.~P. and Jones, M.~C. Kernel smoothing/. Chapman and Hall Ltd., London (1995).

See Also

RK, Kernel characteristics, integrate.

Examples

        ##      Note that lower and upper params are set in the definition to
        ##      use 'dom()' function.
        g <- function(kernels)
        {
                mu0 <- sapply(kernels,function(x) computeMu0(x,))
                mu0.ok <- sapply(kernels,mu0K)
                mu2 <- sapply(kernels,function(x) computeMu(2,x))
                mu2.ok <- sapply(kernels,mu2K)
                Rk.ok <- sapply(kernels,RK)
                RK <- sapply(kernels,function(x) computeRK(x))
                K4 <- sapply(kernels,function(x) computeK4(x))
                res <- data.frame(mu0,mu0.ok,mu2,mu2.ok,RK,Rk.ok,K4)
                res
        }
        g(kernels=c(EpaK,gaussK,TriweigK,TrianK))

[Package locpol version 0.4-0 Index]