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% This code fits makes a linear fit to a data set (using y =bx+a) where each data point
% has a different or constant standard deviation. Your data should have three or two columns.
% The first column should be the independent variable(x) and the second
% column should be the dependent variable(y). Column three should contain
% your standard deviations for each datapoint. In the situations where you
% do not specify a column three, the code assigns a weight of one to all
% data points and this corresponds to the regular linear fits.
%==========
% INPUTS
%==========
%data = 3 columns; column 1 = x, column2 = y and column 3 = standard dev.
%==========
%OUTPUTS
%==========
%Result.slope= b; Fitted slope
%Result.Intercept = a; Fitted intercept
%Coded by Ebo Ewusi-Annan (University of Florida, 2011)
%============
%REFERENCES
%===========
%1. Willam H. Press, Saul A. Teukolsky and Willan T. Vetterling (1997).
%Numerical Recipes in Fortran.
%2. Philip R. Bevington and D. Keith Robinson (2003). Data Reduction and
%Error Analysis for the Physical Sciences.
Cite As
Ebo Ewusi-Annan (2026). Weighted and unweighted linear fit (https://se.mathworks.com/matlabcentral/fileexchange/34352-weighted-and-unweighted-linear-fit), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (1.9 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 |
