DK: Gradient of the kernel function

In Epsilon127/ldder: Local Density Derivative Estimation

Description

DK returns the gradient of K at its argument(s).

Usage

DK(z, type = "Gaussian")

Arguments

z	A vector or matrix containing where the kernel is evaluated. If it is a matrix each column is interpreted as a vector.
type	A character string specify the used kernel function. Current options are "Gaussian" and...

Value

If the input is avector the value DK(z) will be returned as a vector. If the input is a matrix a matrix DK(z_1), …, DK(z_m) will be returned, where z = [z_1, …, z_m].

Examples

z <- rnorm(3)
DK(z, "Gaussian")

Z <- matrix(rnorm(12), 3, 4)
DK(Z, "Gaussian")

Epsilon127/ldder documentation built on March 7, 2020, 7:47 a.m.