kdeC: Two-dimensional fast weighted kernel density estimation

In WPKDE: Weighted Piecewise Kernel Density Estimation

Two-dimensional fast weighted kernel density estimation

Description

Two-dimensional fast weighted kernel density estimation

Usage

kdeC(x, H, gridsize, cutNum, w)

Arguments

x	Data points in the format of an n x 2 matrix.
H	Bandwidth, a vector containing 2 numeric values.
gridsize	Number of points for each direction, a vector containing 2 integer values.
cutNum	Number of pieces to be cut for each direction, a vector containing 2 integer values.
w	Weight, a vector corresponding to parameter 'x'.

Value

A list containing three elements:

estimate	The estimated values of the kernel density.
evalpointsX	The evaluation points along the X direction.
evalpointsY	The evaluation points along the Y direction.

Examples

data(r)
k <- kdeC(r$dat, H = c(0.014, 0.014), gridsize = c(330, 330), cutNum = c(1, 1), w = r$z)

WPKDE documentation built on June 8, 2025, 11:24 a.m.