What is the regress function doing?
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I don't understand what the regress function is returning. My understanding that it should be the gradient of the line of best fit. For example:
x = [1:5]'
y = [2 4 6 8 10]'
b = regress(y, x)
returns b = 2 as expected, whereas:
x = [1:5]'
y = [5 4 3 2 1]'
b = regress(y, x)
returns b = 0.6364 as opposed to -1.
What is the regress function calculating in this case? Where does this value for b come from?
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Accepted Answer
Star Strider
on 24 Dec 2015
The reason the first data set returned the slope you expected is that the intercept was zero, and your design forced a zero intercept. The reason the second data set is not returning -1 for the slope is because you are forcing it to have an intercept at zero.
If you include an intercept term, you get the expected -1 slope with a y-intercept of +6:
x = [1:5]'
y = [5 4 3 2 1]'
b = regress(y, [x ones(size(x))])
b =
-1
6
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