Hi, I am solving an optimization problem using Optimizaiton Toolbox.
I have six parameters which are the rate constants of a model that conforms to the Markov chain. After calculation, I get a matrix, A, containing different states in this model. Then I plot the data in A and fit it in order to get three results I want, suppose they are a, b, c. In order to match the three results of my model with the experimental data, I try to minimize chi-square, which defined to be the squared difference between experimental and model results divided by the experimental results.
In short, I want to find optimal rate constants to minimize chi-square function.
I have tried two different solvers (fminunc, lsqnonlin) with different algorithms, but it didn't seem to work. After running the optimization two hours, these rates only change about 0.003. Is it because of the random values of a, b, c? If so, how can I solve this problem?
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