Least squares regression to find coefficients

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Tyler Bodnarik
Tyler Bodnarik 2020-9-15
回答： Asad (Mehrzad) Khoddam 2020-9-15
Not sure what to do here. I tried doing it all seperately by setting noise to 0, then to 50, then 100 and using polyfit but I get the same answer everytime. I also tried using the backslash.
y(𝑥)=𝑝1+𝑝2𝑥
where
x = 0:0.1:20;
noise =?? % a number, to define
y= 4*x + noise*rand(1,length(x));
Vary the value for noise as 0, 50 and 100 to get three different results for 𝑝1and 𝑝2,
From a linear algebra standpoint, determine the coefficients, 𝑝1and 𝑝2, of the least-squares-regression of a line fit through the data defined above.

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回答（1 个）

Asad (Mehrzad) Khoddam
one solution is:
[length(x) sum(x); sum(x) sum(x.^2)]\[sum(y) ; sum(x.*y)]

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