Of course, the linear least-square regression is an easy thing to do in Excel. Just adding a linear trend-line to the plot will do that for you. Anyway, I wrote this piece of code to do it in Matlab.
% Single least-square linear regression
%Created on 02/17
x=input ('x='); %use [] to input a row
y=input ('y='); %use [] to input a row
X=mean(x);
Y=mean(y);
beta=(sum((x-X).*(y-Y)))/sum((x-X).^2);
alpa=Y-beta*X;
Equation=strcat('y=',num2str(beta), 'x+',num2str(alpa))
The num2str function was used to convert the beta and alpa, which are numbers, into strings.
The strcat function was used to concatenate the strings.
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You can also calculate the least squares coefficients by using MATLAB's backslash operator to "divide" the dependent variable by the independent variables:
ReplyDeleteCoeff = Input \ Output;
See my posting on this at:
http://matlabdatamining.blogspot.com/2007/04/linear-regression-in-matlab.html