Info

This question is closed. Reopen it to edit or answer.

Bug in MATLAB R2014b

1 view (last 30 days)
Nikhil
Nikhil on 3 Feb 2016
Closed: MATLAB Answer Bot on 20 Aug 2021
Hello all,
I am doing regression analysis using Curve Fitting tool available in MATLAB. Aim is to find a polynomial function between 2 design variables and 1 response i.e. z=f(x,y). I used robust regression methods from curve fitting tool box and fitlm(,,'RobustOpts','on') function. Both of them gives same estimates for polynomial coefficients but different R-square and adjusted R-square values. So can somebody please tell me which one of them is correct? Is the R-square (for robust regression) from curve fitting tool is more accurate or one from fitlm(,,'RobustOpts','on') function is more accurate? Please let me know, Thank you in advance,
Nik

Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!