MATLAB: Matlab nonlinear regression

chris

I have never used matlab, and i need help with a nonlinear regression problem, ive looked up the nlinfit funtction help but I dont understand it a lot.

I have mi I data, and my V data. i have my plot. Now im supposed to do an nonlinear regression as far as i understand thi is my function

I(V)=Ix-Ix(V/Vx)^(n+q) I know I and V but i need to find Ix,(n+q) and V. I'll appreciated if someone can help out.

Best Answer

You need to make a function of two variables b and V. The three elements of b are the three unknowns lx, (n+q), and Vx. Note that, as given, there's no way to determine n and q individually, only the sum. Once you have the function foo(b,V), pass that to nlinfit, with an initial guess at b

b = nlinfit(Vdata,Idata,@foo,[pi;42;0])

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MATLAB: How to replace values in a matrix

Try a simple for loop:

A=[ 0.2 0.07 0.25 0.87 0.09 0.14 0.8 0.3;
  0.1 0.5 0.25 0.14 0.98 0.025 0.58 0.11;
  0.001 0.25 0.88 0.21 0.03 0.25 0.58 0.25;
  0.26 0.58 0.001 0.06 0.9 0.58 0.44 0.15;
  0.12 0.58 0.16 0.08 0.15 0.47 0.33 0.15;
  0.15 0.22 0.3 0.14 0.01 0.99 0.77 0.55;
  0.003 0.25 0.14 0.99 0.005 0.85 0.26 0.003;
  ];
B=[ 0.25 0.55 0.15 0.02;
  0.001 0.25 0.33 0.04;
  0.2 0.3 0.11 0.58;
  0.25 0.14 0.77 0.69;
  0.88 0.59 0.58 0.001;
  0.02 0.3 0.7 0.8;
  0.3 0.9 0.66 0.11;]
C= [ 8 2 4 1
  1 2 3 4
  7 5 2 8
  1 2 3 4
  2 4 3 7
  1 5 6 7
  2 8 4 1]
[rows, columns] = size(B)
newA = A; % Initialize.
for row = 1 : rows
  newA(row, C(row,:)) = B(row, :);
end
newA % Print in command window to verify

MATLAB: Nonlinear regression

From the doc: "nlintool(X,y,fun,beta0) is a graphical user interface to the nlinfit function, and uses the same input arguments"

IOW, nlintool is just a user-friendly front-end to the nlinfit function.

The error is a standard MATLAB error for array operations versus matrix operations. Multiply, divide, and exponentiation are all interpreted in a matrix sense; to use an array operation (ie element-by-element), precede the operator with a dot:

chris = b1-b1*(X/b2).^b3;

Beyond that, you're also going to run into other problems, so let me make a preemptive strike...

Don't define your data in this function!

X and beta are passed in to the function as arguments. Y isn't needed at all here. The function simply defines the model you're trying to fit. Given a value of X and parameters beta, it should return the value of the model you're fitting (ie yhat = beta1 - beta*(X/beta2)^beta3).

It is nlinfit that needs the measured X and Y data values. It ( nlinfit ) uses these to compare the model's predictions for the given X values to the given Y values. It then adjusts the parameters to get the best fit.

So: remove all data from the function. Move them into a separate script. Then, in that script, call nlinfit with an initial guess for beta ( beta=[1.4 0.537 1.1] ).

Best Answer

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MATLAB: How to replace values in a matrix

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