Linear Regression Matlab code
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Ryan Albawab
le 26 Avr 2015
Commenté : Or Hirshfeld
le 27 Avr 2015
Hello, this is my matlab script that is supposed to take data from an excel spread sheet and use it to create a y = mx+b function by linear regression. Here is my code and attached is the excel spread sheet. The first row is the amount in gallons and the next two rows are the amount of time it took to move the gallons in seconds.
points = xlsread('data.xlsx');
n = size(points,1);
sum_x = 0;
sum_y = 0;
sum_xy = 0;
sum_x2 = 0;
for i = i:n
sum_x = sum_x + points(i,2);
sum_y = sum_y + points(i,3);
sum_xy = sum_xy + points(i,2)*(points(i,3));
sum_x2 = sum_x2 + (points(i,2)^2);
end
a1 = (n*sum_xy - sum_x*sum_y)/(n*sum_x2 - sum_x2);
a0 = (sum_y/n)-a_1*(sum_x/n);
y_new = a1*x + a_0;
THank you for your help.
5 commentaires
Image Analyst
le 27 Avr 2015
You haven't defined your x variable yet, like Mohammad did where he called x "gModel" - a more descriptive name than the generic "x". It looks like his code should work. If it does, Vote for it and then click "Accept this answer" .
Or Hirshfeld
le 27 Avr 2015
I would use curve fitting function in matlab instead of summing in iterations and calculated formulas.
Réponse acceptée
Mohammad Abouali
le 27 Avr 2015
% First COLUMN is galon, the next two columns are amount of time required
% to remove that amount of gallons. I assumed you have two sets of
% measurements that's why there are two columns.
data=[ 0.50 66 70; ...
0.75 100 95; ...
1.00 129 135; ...
1.25 161 159; ...
1.50 198 190; ...
1.75 230 232; ...
2.00 265 250];
% Fitting a a polynomial t=a1*g+a0; g: Gallon, t: time
g=[data(:,1);data(:,1)];
tMeasured=[data(:,2);data(:,3)];
a=polyfit(g, tMeasured,1);
% Plot1
gModel=min(g):0.01:max(g);
tModelled=polyval(a,gModel);
figure
plot(gModel,tModelled,'r-','LineWidth',2);
hold on
plot(g,tMeasured,'kx','MarkerSize',10)
legend('Fitted Line','Measured','Location','NorthWest');
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