The Sequential Simplex Approach to Optimisation
John Ogilvie, CECM
Although Maple has for several years contained procedures for constrained optimization according to linear programming, another approach involving simplices is applicable to non-linear regression. Traditionally the latter approach provides no estimates of uncertainty of parameters, but E. Romero and I have extended a procedure in Maple to encompass this capability. I shall demonstrate with animations the application of this approach to real and simulated data.