I have 2 sets of data of the same size (X1, Y1) and (X2,Y2). (X1,Y1) has a linear relationship with zero intercept (Y1=slope*X1). How can I estimate the slope, R^2 value and plot it along with 95% confidence interval lines? Using Corrcoeff, polyfit and polyval gives me a relationship of the form Y1=slope*X1 + c, but I would like to force c=0.
(X2,Y2) has a non-linear relationship of the form Y2=A-Bexp(C*X2). Likewise, I would like to determine A,B & C along with R^2 value and plot it along with 95% confidence interval lines. I know I have to use nlinfit, nlparci but I am new in this and would need your help.
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You seem to be acquainted with nlinfit and know how to use it, but apparently not with Anonymous Functions.
I suggest you use nlinfit for both problems. With B = [B(1) ... B(n)]' a column vector of parameters, your Y1 function becomes:
Y1 = @(B,x) B.*x;
since with only one parameter in it, you do not need to use subscripts.
Your Y2 function becomes:
Y2 = @(B,x) B(1)-B(2).*exp(B(3).*x);
These should work as your modelfun functions in nlinfit.
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