Function value and YDATA sizes are not equal. Can anyone help?

n=100;
xdata = linspace(0.3,10,n);
ydata = 1./(0.1*xdata) + 2 + 0.1*randn(n) ;
fun = @(x,xdata)1./(x(1).*xdata) + x(2);

x0 = [0.1 , 1];
x = lsqcurvefit(fun,x0,xdata,ydata)
times = linspace(xdata(1),xdata(end));
plot(xdata,ydata,'ko',times,fun(x,times),'b-')
legend('Data','Fitted exponential')
title('Data and Fitted Curve')

Answer 1

[Star Strider]

The problem is the randn call. With one argument, it creates an (nxn) matrix, not a vector, so of course the sizes will not match. Adding another argument to create it as a (1xn) vector and it works —

n=100;
xdata = linspace(0.3,10,n);
ydata = 1./(0.1*xdata) + 2 + 0.1*randn(1,n) ;
fun = @(x,xdata)1./(x(1).*xdata) + x(2);

x0 = [0.1 , 1];
x = lsqcurvefit(fun,x0,xdata,ydata)

Local minimum found.

Optimization completed because the size of the gradient is less than
the value of the optimality tolerance.

x = 1×2

0.1001 1.9965

times = linspace(xdata(1),xdata(end));
plot(xdata,ydata,'ko',times,fun(x,times),'b-')
legend('Data','Fitted exponential')
title('Data and Fitted Curve')

.