mvlinbin: Multivariate Linear Binning

In bpkde: Back-Projected Kernel Density Estimation

Description

Compute a binned approximation of the data on a regularly spaced grid using the multivariate linear binning rule described in Wand (1994).

Usage

mvlinbin(X, r = 7, padding)

Arguments

X	a numeric matrix.
r	a positive integer value. The number of grid points M in each dimension is given by M = 2^r.
padding	a numeric vector of positive values with length equal to the number of columns of X specifying the amount of zero-padding added to each coordinate direction. No padding is added when this argument is missing.

Value

a list with class mvlinbin containing the following elements.

axes	a numeric matrix whose columns contain the grid points used along each axis to bin the data.
xi	a numeric array containing the binned approximation of the data.
X	a numeric matrix containing the input data.
deltas	a numeric vector containing the grid spacing.
M	an integer value giving the number of grid points used in each coordinate direction.
n	an integer value containing the number of data points binned.
d	an integer value giving the dimensionality of the data.

Author(s)

Kjell Konis [e-mail]

References

Wand, M. P. (1994). Fast Computation of Multivariate Kernel Estimators. Journal of Computational and Graphical Statistics, 3, 433-445.

bpkde documentation built on May 2, 2019, 10:25 a.m.