Hi,
I understand that you want to find Optimal Parameters of a Definite Integral Function. The issue you are encountering is because MATLAB’s "integral" function expects the upper and lower bounds of the "integral" to be scalars, not vectors. However, in the provided code “xIn” is passed as upper bound, which is a vector. To resolve this, the code should be modified to process each data point separately, accumulating the squared errors from all points. This involves iterating through each data point, evaluating the integral with the specific “x” value as the upper bound, and then calculating the squared error.
Below is the modified code to accomplish this:
fun = @(D) sum(arrayfun(@(x, y) (integral(@(t)(D(1)*t.^2 + D(2)*t + D(3)).^-m, x0, x) - y)^2, xIn, yIn));
D0 = [1 1 1];
D = lsqnonlin(fun, D0);
I hope this helps!
