NAME

       gbnlpanel - Non-linear panel regression

SYNOPSIS

       gbnlpanel [options] <FUN>

DESCRIPTION

       Each  row  of a block represents a single process realization. Blocks are separated by two
       white spaces and represent model variables, columns represent the time variable. Input  is
       read  as (X1_[r,t],...,Xj_[r,t],...  XN_[r,t]), where r is the row, t the column and j the
       block. The model assumes that

       FUN(X1_[r,t],...,XN_[t,t]) - c_r = e_{r,t}

       with e i.i.d and 'c' arow specific element, which can be fixed (fixed effect) or a  normal
       random variable (random effect).

OPTIONS

       -M     type of model (default 0)

       0      fixed effects

       1      random effects

       -O     type of output  (default 0)

       0      parameters

       1      parameters and errors

       2      <variables> and panel statistics

       3      parameters and variance matrix

       -V     variance matrix estimation (default 0)

       0      < J^{-1} >, computed via fully-reduced log-likelihood

       1      < H^{-1} >, computed via fully-reduced log-likelihood

       2      < H^{-1} J H^{-1} >, computed via fully-reduced log-likelihood

       3      < J^{-1} >, computed via non-reduced log-likelihood

       4      < H^{-1} >,  computed via non-reduced log-likelihood

       5      < H^{-1} J H^{-1} >, computed via non-reduced log-likelihood

       -v     verbosity level (default 0)

       0      just results

       1      comment headers

       2      summary statistics

       3      covariance matrix

       4      minimization steps

       5      model definition

       -e     minimization tolerance (default 1e-6)

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

       -h     this help

       -A     comma  separated  MLL optimization options: step,tol,iter,eps,msize,algo. Use empty
              fields for default.  (default 0.1,0.01,500,1e-6,1e-6,0)

       step   initial step size of the searching algorithm

       tol    line search tolerance iter: maximum number of iterations

       eps    gradient tolerance : stopping criteria ||gradient||<eps

       algo   optimization     methods:     0     Fletcher-Reeves,     1     Polak-Ribiere,     2
              Broyden-Fletcher-Goldfarb-Shanno,  3 Steepest descent (not recommended), 4 simplex,
              5 Broyden-Fletcher-Goldfarb-Shanno-2

EXAMPLES

       gbnlpanel 'x1-a*x2-c,a=0,c=0' < data.dat
              linear panel regression with one independent variable

AUTHOR

       Written by Giulio Bottazzi

REPORTING BUGS

       Report bugs to <gbutils@googlegroups.com>

       Package home page <http://cafim.sssup.it/~giulio/software/gbutils/index.html>

COPYRIGHT

       Copyright © 2001-2018 Giulio Bottazzi This program is free software; you can  redistribute
       it  and/or  modify  it  under  the  terms of the GNU General Public License (version 2) as
       published by the Free Software Foundation;

       This program is distributed in the hope that it will be useful, but WITHOUT ANY  WARRANTY;
       without  even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
       See the GNU General Public License for more details.