mslr(Y, X, window, [minPeriods])
Please see Moving Functions (m-functions) for the parameters and windowing logic.
Conduct the simple least-squares regressions of Y on X in a sliding window.
The result is a tuple of two vectors. The first vector is the intercepts and the second vector is the coefficient estimates of X.
$ Y=1 4 3 9 5 4 $ X=12 31 29 88 67 76 $ mslr(Y,X,4); ([,,,0.177052,0.712557,0.15],[,,,0.101824,0.084418,0.078462])