nlinfit fitting error approaching infinity

I am trying to run the code below:

However I am getting the error:

Error using nlinfit>checkFunVals (line 649)

The function you provided as the MODELFUN input has returned Inf or NaN values.

Error in nlinfit>LMfit (line 620)

if funValCheck && ~isfinite(sse), checkFunVals(r); end

Error in nlinfit (line 284)

[beta,J,~,cause,fullr] = LMfit(X,yw, modelw,beta,options,verbose,maxiter);

How can I solve this issue

A(:,:,1) = [1.17	1.2     1.22	1.23	1.25	1.27
            1.18	1.21	1.22	1.23	1.25	1.25
            1.19	1.21	1.22	1.23	1.24	1.24
            1.2     1.22	1.22	1.22	1.23	1.22
            1.2 	1.21	1.22	1.22	1.22	1.22
            1.2     1.21	1.21	1.21	1.21	1.2
            1.2     1.2 	1.2     1.2     1.2 	1.19];

A(:,:,2)=[  1.22	1.26	1.31	1.33	1.37	1.39
            1.26	1.29	1.32	1.33	1.36	1.37
            1.27	1.3     1.32	1.33	1.36	1.36
            1.28	1.31	1.33	1.34	1.35	1.34
            1.29	1.31	1.32	1.33	1.34	1.33
            1.29	1.3     1.31	1.32	1.32	1.31
            1.29	1.3     1.31	1.31	1.31	1.29];

A(:,:,3) = [1.29	1.34	1.37	1.41	1.45	1.47
            1.31	1.36	1.4 	1.42	1.44	1.45
            1.33	1.38	1.41	1.41	1.43	1.43
            1.35	1.39	1.41	1.41	1.42	1.41
            1.35	1.39	1.41	1.41	1.41	1.4
            1.36	1.38	1.4 	1.39	1.4     1.38
            1.36	1.38	1.39	1.39	1.39	1.37];


K = 60:10:120;
C = [0 0.1 0.2 0.3 0.6 0.9];
X = [7 10 13.5].^2/100^2;

[c, k, x] = meshgrid(C, K, X);

% % % MAPPING: x = ckx(:,1),  y = ckx(:,2),  z = ckx(:,3),  a = b(1),  b= B(2),  c = b(3),  d = b(4)
ckx = [c(:) k(:) x(:)];

Eq = @(b,ckx) ((b(8).*ckx(:,2).*ckx(:,1)) + 1).*(b(1).*ckx(:,2) + b(2).*(ckx(:,1)).^b(3)).* ckx(:,3).^(b(4).*ckx(:,2)+b(5).*(ckx(:,1)+1).^b(6)) + b(7);
B = nlinfit(ckx, A(:), Eq, [0.01, 1, 1, 0.01, 0.1, 0.1, 0.1, 0.00001]);


plot(A(:)); hold on;  plot(A(:)-R)
xticks([4:7:126])
xticklabels([0	0.1	0.2	0.3	0.6	0.9 0	0.1	0.2	0.3	0.6	0.9 0	0.1	0.2	0.3	0.6	0.9])

Answer 1

[Deepak Meena]

Hi Muhannad Fadhel,

From my understanding , your initial values of the parameters seems to be problem since you are using exponential terms

Using this answer, I changed the initial values to

[0.01, 1, 0.09, 0.0018, 0.1, 0.19, 0.1, 0.00001]

It doesn't give the Nan or Inf error but this might not be the best starting values you neeeded for your dataset.