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gbkreg - Kernel non linear regression function


gbkreg [options]


Kernel estimation of conditional moments. Data are read from standard input as couple
(x,y). The moments of y are computed on a regular grid in x. The kernel bandwidth, if not
provided with the option -H, is set automatically.


-n number of equispaced points where moments are computed (default 64)

-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

-M choose the method to compute the density (default 1)

0 FFT (number of points rounded to nearest power of 2)

1 discrete convolution (only with compact kernels)

2 explicit summation (can be long)

-O set the output, comma separated list of m mean, v standard deviation, s skewness
and k kurtosis (default m)

-v verbose mode

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

-h this help


gbkreg -M 2 < file
compute the kernel regression of the entries in the second column of 'file' vs. the
entries in the first column. If more data columns exist in file they are ignored.
Explicit summation method (slower) is used.

gbkreg -02 < file
compute the kernel regression of the standard deviation of the entries in the
second column of 'file' vs. the entries in the first colum

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