Orthogonal Linear Regression
No License
% Orthogonal linear least square fit of xdata and ydata vectors
% p=linortfit(xdata,ydata) gives the the coefficient-vector p that
% corresponds to the linear expression: y=p(1)+p(2)*x, where p
% is minimized with respect to the objective function
% sum((p(1)+p(2)*xdata-ydata).^2/(1+p(2)^2)).
%
% Example:
%
% %prepare some data
% xdata=0:0.1:10;
% ydata=2+7*xdata+6*randn(size(xdata));
% %orthogonal linear fit
% p=linortfit(xdata,ydata)
% yy=p(1)+p(2)*xdata;
% %compare with normal linear regression
% p0=polyfit(xdata,ydata,1);
% yy0=polyval(p0,xdata);
% %plot to compare data with linear fits
% plot(xdata,ydata,'.',xdata,yy,xdata,yy0,':');
Cite As
Per Sundqvist (2024). Orthogonal Linear Regression (https://www.mathworks.com/matlabcentral/fileexchange/6716-orthogonal-linear-regression), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Acknowledgements
Inspired: Orthogonal Linear Regression
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
Version | Published | Release Notes | |
---|---|---|---|
1.0.0.0 |