Orthogonal regression fitting in scipy least squares method

Question

The leastsq method in scipy lib fits a curve to some data. And this method implies that in this data Y values depends on some X argument. And calculates the minimal distance bet

Answer 1

I've found the solution. Scipy Odrpack works noramally but it needs a good initial guess for correct results. So I divided the process into two steps.

First step: find the initial guess by using ordinaty least squares method.

Second step: substitude these initial guess in ODR as beta0 parameter.

And it works very well with an acceptable speed.

Thank you guys, your advice directed me to the right solution