| Group: | Optimizer |
| See also: | bfgs |
| Function: | nelmin | |
| Description: | nelmin searchs a minimum of a function. In each iteration step the function is evaluated at a simplex consisting of p+1 points. The simplex contracts until the variance of the evaluated function values is less than eps (or the maximal number of iterations is reached). |
| Usage: | x = nelmin (x0, f, maxiter {,eps , step}) | |
| Input: | ||
| x0 | p x n matrix with n starting vectors | |
| f | text, name of the procedure where the function is defined | |
| maxiter | integer, maximal number of iterations | |
| eps | scalar | |
| step | scalar, lenght of initial simplex | |
| Output: | ||
| x.minimum | p x n matrix with the n minima | |
| x.iter | number of iterations | |
| x.converged | 1 if the algorithm has converged with every starting vector and 0 if it has not | |
proc (y) = f (x) y = sum(x^2) endp x0 = #(1,1,1)~#(1,2,3) nelmin (x0, "f", 100, 1.0e-6)
Contents of nelmin.minimum [1,] 0.017404 -0.02019 [2,] -0.0070216 0.022459 [3,] 0.016622 0.0042336 Contents of nelmin.iter [1,] 53 Contents of nelmin.converged [1,] 1
| Group: | Optimizer |
| See also: | bfgs |