Hello, I need an efficient way to performs linear regression because I have to fit several segments in a big for loops which takes time to achieve. In the past, their was a linreg function which has been depreciated. Currently I am using polyfit to do a polynomial fit of order 1, for each segment. …

[image] Paul_Soderlind: I have recently noticed that b=(x'x)\(x'y) is often twice as fast as b = x\y , for instance, when x is 1000x10 and y is 1000x1 . So far, I have no good explanation for it. Sorry to come late to this thread, but I’m surprised that no one seems to have given the correct …

what about? using Random N = 10000 x = rand(N) X = [ones(N) x] y = 10 .+ x .* 0.3 function linreg1(y, X) β_hat = (X' * X) \ X' * y return(β_hat) end function linreg2(y, X) β_hat = X \ y return(β_hat) end using GLM GLM.fit(LinearModel, X, y, true) using DataFrames, GLM data = Da…

First you should decide what you want the function to be. Here you are assuming that the model matrix X has been externally created. I believe the original suggestion was to have two vectors, x and y, as the arguments. In that case it is best to go old school and create X'X and X'y without ever c…

Sounds like a pretty strong case for having an efficient linreg function in the Statistics stdlib.

Wouldn’t you always have to create X externally in a for loop?

I’m not sure I understand the question. If you have the vector x and you want X'X and X'y you don’t need to allocate and populate the N by 2 matrix X. That’s what the section in the code with Symmetric([T(N) sum(x); zero(T) sum(abs2, x)], :U) and [sum(y); dot(x, y)] is doing. Once upon a time…

I just learned so much from just those two lines! Thank you! I didn’t even know there was such a thing…

does x’ mean the derivative of x? and is x independent, while y is dependent?

x’ means transpose of x in this context. If we were talking about odes it’d probably mean x’(t)

Sorry to bring this discussion back. But I think that many times the user is just searching for a function which given two vectors x and y, returns the coefficients of the linear fit and the Pearson correlation coefficient, and perhaps a third vector with the fitted Y values in the same x positions,…

Efficient way of doing linear regression

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Juan August 12, 2020, 11:26pm 42

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Efficient way of doing linear regression

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