[x0,v,nev] = nelder_mead_min (f,args,ctl) - Nelder-Mead minimization

 Minimize 'f' using the Nelder-Mead algorithm. This function is inspired
 from the that found in the book "Numerical Recipes".

 ARGUMENTS
 ---------
 f     : string : Name of function. Must return a real value
 args  : list   : Arguments passed to f.
      or matrix : f's only argument
 ctl   : vector : (Optional) Control variables, described below
      or struct

 RETURNED VALUES
 ---------------
 x0  : matrix   : Local minimum of f
 v   : real     : Value of f in x0
 nev : number   : Number of function evaluations
 
 CONTROL VARIABLE : (optional) may be named arguments (i.e. "name",value
 ------------------ pairs), a struct, or a vector of length <= 6, where
                    NaN's are ignored. Default values are written .
  OPT.   VECTOR
  NAME    POS
 ftol,f  N/A    : Stopping criterion : stop search when values at simplex
                  vertices are all alike, as tested by 

                   f > (max_i (f_i) - min_i (f_i)) /max(max(|f_i|),1)

                  where f_i are the values of f at the vertices.  <10*eps>

 rtol,r  N/A    : Stop search when biggest radius of simplex, using
                  infinity-norm, is small, as tested by :

              ctl(2) > Radius                                     <10*eps>

 vtol,v  N/A    : Stop search when volume of simplex is small, tested by
            
              ctl(2) > Vol

 crit,c ctl(1)  : Set one stopping criterion, 'ftol' (c=1), 'rtol' (c=2)
                  or 'vtol' (c=3) to the value of the 'tol' option.    <1>

 tol, t ctl(2)  : Threshold in termination test chosen by 'crit'  <10*eps>

 narg  ctl(3)  : Position of the minimized argument in args            <1>
 maxev ctl(4)  : Maximum number of function evaluations. This number 
                 may be slightly exceeded.
 isz   ctl(5)  : Size of initial simplex, which is :                   <1>

                { x + e_i | i in 0..N } 
 
                Where x == args{narg} is the initial value 
                 e_0    == zeros (size (x)), 
                 e_i(j) == 0 if j != i and e_i(i) == ctl(5)
                 e_i    has same size as x

                Set ctl(5) to the distance you expect between the starting
                point and the minimum.

 rst   ctl(6)   : When a minimum is found the algorithm restarts next to
                  it until the minimum does not improve anymore. ctl(6) is
                  the maximum number of restarts. Set ctl(6) to zero if
                  you know the function is well-behaved or if you don't
                  mind not getting a true minimum.                     <0>

 verbose, v     Be more or less verbose (quiet=0)                      <0>

Package: optim