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gbkreg2d - Kernel non linear regression for bivariate data

Author

       Written by Giulio Bottazzi

Description

       2D  kernel  estimation  of conditional moments. Data are read from standard input as triplet (x,y,z). The
       moments of z are computed on a regular grid in x and y The kernel bandwidth  if  not  provided  with  the
       option -H is set automatically.  Different bandwidths can be specified for x and y. Different moments are
       given  in  different  data  block.  Options  -n,  -f,  -H and -S accept comma separated values to specify
       different values for x and y components

Name

       gbkreg2d - Kernel non linear regression for bivariate data

Options

-n     number of points where the estimation is computed (default 10)

       -f     fraction of the support for which to print the result (default .9)

       -H     set the kernel bandwidth explicitly

       -S     scale the kernel bandwidth with respect to heuristic 'optimal'

       -K     choose the kernel: 0 Epanenchnikov, 1 Rectangular, 2 Silverman type I 3 Silverman type II (default
              0)

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

       -D     switch off data de-variation procedure

       -v     verbose mode

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

       -h     this help

Reporting Bugs

Synopsis

gbkreg2d [options]

See Also