Linear binning for multivariate data

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Description

Linear binning for 1- to 4-dimensional data.

Usage

1
binning(x, H, h, bgridsize, xmin, xmax, supp=3.7, w, gridtype="linear")

Arguments

x

matrix of data values

H,h

bandwidth matrix, scalar bandwidth

xmin,xmax

vector of minimum/maximum values for grid

supp

effective support for standard normal is [-supp,supp]

bgridsize

vector of binning grid sizes

w

vector of weights. Default is a vector of all ones.

gridtype

not yet implemented

Details

As of ks 1.10.0, binning is available for unconstrained (non-diagonal) bandwidth matrices. Code is used courtesy of A. & J. Gramacki, and M.P. Wand. Default bgridsize are d=1: 401; d=2: rep(151, 2); d=3: rep(51, 3); d=4: rep(21, 4).

Value

Returns a list with 2 fields

counts

linear binning counts

eval.points

vector (d=1) or list (d>=2) of grid points in each dimension

References

Gramacki, A. & Gramacki, J. (2015) FFT-based fast computation of multivariate kernel estimators with unconstrained bandwidth matrices. URL: arxiv.org/abs/1508.02766.

Wand, M.P. & Jones, M.C. (1995) Kernel Smoothing. Chapman & Hall. London.

Examples

1
2
data(unicef)
ubinned <- binning(x=unicef)

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