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.

normal-bracket44bracket-normal 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 0.2-0 Index]