Im running MATLAB 2010B and have the optimization toolbox (but not the global optimization toolbox).
I am not sure if I can use interpn.m for my problem.
I have a dependant variable, stored in a 1xK vector. (R)
I have a number (lets say 5) of independant variables stored in seperate 1xK vectors. (L1, L2, L3..L5)
I also have 5 "current" observations for the independant variables. (va, vb, vc...)
I would like to use somekind of optimization/ lookup routine to find the likely value of the dependant variable, r_now.
r_now = myFunc(L1, L2, L3, L4, L5, R, va, vb, vc, vd, ve);
I thought interpn.m might work for myFunc, but I cant get it to. Does anyone have any experince with this function?
None of my variables are montonically increasing, or on a regular grid, and the relationship is quite rough, so I thought the spline option from interpn.m would be useful.
When I place a breakpoint at the start of vi = interpn(varargin) I see (using 3 independants):
[8286x1 double] [8286x1 double] [8286x1 double] [8286x1 double] [0.5000] [0.5000] [0.5000] 'spline'
I get the error message
??? Error using ==> interpn at 155 Wrong number of input arguments or some dimension of V is less than 2.
If interpn.m is not a good approach, can anyone suggest one? It needs to be quick (i.e. not simulated annealing/ stochastic methods)