Hi There,
i want to use 'Multistart' to find the best solution for a bi-exponential decay function that i am fitting to my data with bounds.
Below is the code i am using.
% bi-exponential decay model
fparam = fittype(@(a,b,c,d,x)(a)*exp(-(1/b)*x)+abs(1-a)*(exp(-(1/c)*x))+d); lb1 = [0,0,0,0]; ub1 = [1,30,200,80]; b0 = [0.3,0.2,20,10]; x = [3.39,8.59,13.8,19,24.2,29.4,34.6,39.81,45.0,50.21]; y = [1,0.2905,0.0894,0.0838,0.1173,0.1006,0.0782,0.0894,0.1061,0.0726] opts = fitoptions('Display','Off','Method','NonlinearLeastSquares','Normalize','Off',... 'Startpoint',b0, 'Robust','On','Lower',lb1,'Upper',ub1,... 'TolFun',1e-3); [estTmp,Goft,Out] = fit(x,y,fparam,opts);Since i need to start somewhere i have randomly chosen 'b0' values. I want to avoid local minima, so i want to use 'Multistart' function for optimization and find the best solution within the 'bounds' (here given by 'lb1', 'ub1').
Can someone please help me bridge 'Multistart' with 'fit' ?
P.S. I know someone might suggest to use 'lsqnonlin' instead of 'fit'. The reason i am not using it is becasue i need the output 'stats' (e.g. goodness of fit and R^2 values) which i might have to compute manually in 'lsqnonlin'. So please suggest me only the ways to combine 'Multistart' and 'fit'
Best Answer