regress(x,y) for least square regression of two variables x,y

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mohamed
mohamed 2013-6-2
when i use regress(x,y),I obtain only one answer :shouldn't i get two answers which are the slope and y-intercept ?

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the cyclist
the cyclist 2013-6-2
You don't show us your code, but I am guessing you neglected to add a column of ones to your x input, as described in the documentation:
doc regress
This code will give you the two-parameter output you expect:
x = [ones(3,1),rand(3,1)];
y = rand(3,1);
b = regress(y,x)
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the cyclist
the cyclist 2013-6-2
@Image Analyst, I answered there, too, and did not realize it was the same poster! sigh
the cyclist
the cyclist 2013-6-2
b = regress(z',[ones(4,1) x' y']);
combines x and y into one array, adds the column of ones that you need, and then does the regression with z.

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Image Analyst
Image Analyst 2013-6-2
I don't have regress(). Please list what Product (toolbox) is is in below your question in the Product box.
You can use polyfit() which is in base MATLAB to get the slope and intercept in one line. Here's a full blown demo:
clc;
% Create training data:
x = [1 4 5 6]
y = [4 6 7 9]
% Do the regression.
coefficients = polyfit(x, y, 1); % 1 means a line
slope = coefficients(1)
intercept = coefficients(2)
% We're done!
% Plot training data:
plot(x, y, 'bo', 'LineWidth', 3);
hold on;
% Plot fit
numberOfPoints = 100;
fitX = linspace(min(x), max(x), numberOfPoints);
fitY = polyval(coefficients, fitX);
plot(fitX, fitY, 'r-', 'LineWidth', 3);
grid on;
xlabel('X', 'FontSize', 30);
ylabel('Y', 'FontSize', 30);

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