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gbker - Produce kernel density estimation


gbker [options]


Compute the kernel density estimation on an equispaced grid. Data are read from standard
input. The kernel bandwidth, if not provided with the option -H, is set automatically
using simple heuristics. Normally the whole support is displayed. The option -w can be
used to restrict the computation to specific range of values. The method used to compute
the density is set by the option -M. The boundaries of the grid are slightly different in
the different cases.


-n number of equispaced points/bins where the density is computed (default 64)

-w set the grid boundaries with min,max (default whole support)

-H set the kernel bandwidth

-S scale the automatic kernel bandwidth

-K choose the kernel to use (default 0)

0 Epanenchnikov

1 Rectangular

2 Gaussian

3 Laplacian

-M choose the method for density computation (default 0)

0 use FFT (# grid points rounded to nearest power of 2)

1 use discrete convolution (compact kernels only; bins>2)

2 explicit summation (boundaries excluded)

-F specify the input fields separators (default " \t")


gbker -n 128 -K 2 < file
use a Gaussian kernel to compute the density on 128 equispaced points with the FFT
approach. All the data in 'file' are used, multiple columns are pooled.

gbker -K 3 -M 2 < file
use a Laplacian kernel to compute the density on 64 points. The method used is the
explicit summation.

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