Provided by: gbutils_5.7.1-1_amd64 bug


       gbnlpolyit - Non linear polyit regression


       gbnlpolyit [options] <function definition>


       Non linear polyit estimation. Minimize the negative log-likelihood

              sum_{h=0}^{L-1} log(A+h) - sum_{l=1}^L sum_{h=0}^{n_l-1} log(a_l+h)

       for the Polya specification or

              L log(A) - sum_{l=1}^L n_l log(a_l)

       for  the  multinomial  specification,  where  A  =  sum_{l=1}^L a_l and L is the number of
       alternatives. The input data file should contain L rows, one for each alternative, of  the
       type n x1 ... XN. The first column contains the dependent variable (# of observations) and
       the other columns the  independent  variables.  The  model  is  specified  by  a  function
       a_l=g(x1,x2...)  where x1,.. XN stands for the first, second .. N-th column of independent


       -O     type of output (default 0)

       0      parameters and log-like (ll)

       1      marginal effects

       2      marginal elasticities

       3      n_l n*_l a*_l  *=estimated

       4      occupancies classes

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

       -V     standard errors and p-scores of diff. from zero using bootstrap

       -r     number of replicas (default 20)

       -v     verbosity level (default 0)

       0      just results

       1      comment headers

       2      summary statistics

       3      covariance matrix

       4      minimization steps

       5      model definition

       -R     set the rng seed (default 0)

       -M     set the model to use (default 0) |

       0      Polya

       1      multinomial

       -A     MLL   optimization   options   (default   0.01,0.1,100,1e-6,1e-6,5)   fields    are
              step,tol,iter,eps,msize,algo. Empty fields for default

       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,    4    simplex,    5


       Written by Giulio Bottazzi


       Report bugs to <>

       Package home page <>


       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.