I have a (homegrown) tool which takes a set of data points and finds the best-fit parabola by finding a rotation angle which gives the best vertical parabola by fitting the rotated data to a standard $ax^2 + bx + c$ form. My answer then can generate the putative parabola only by rotating by $\theta$ after generating the vertical parabola. That is, for $ y(x) = ax^2 + bx + c $ , the final curve is
$x' = x*cos(\theta) - y(x)*sin(\theta) $
$y' = x*sin(\theta) + y(x)*cos(\theta) $
What I'm looking for is an algorithm to convert the parameter set $ {(\theta,a,b,c)} $ to the form $ Ax^2 + Bxy + Cy^2 + Dx +Ey + F = 0$ .
Note: yes, I got into this mess by trying to write a Q&D fitting function rather than doing a nonlinear matrix minimization over $\{A,B,C,D,E,F\}$ .
conicfitto CRAN. https://cran.r-project.org/web/packages/fitConic/index.html Not to be confused withfitconic, which has some errors and bugs. – Carl Witthoft Apr 27 '23 at 13:22