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gbkreg - Kernel non linear regression function

Author

       Written by Giulio Bottazzi

Description

       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.

Examples

       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

Name

       gbkreg - Kernel non linear regression function

Options

-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

Reporting Bugs

Synopsis

gbkreg [options]

See Also