Description Usage Details Value
Solves the generalized least squares problem.
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Given matrices a, x, v, glssoln
computes y such that
(x-ay)^T v^{-1} (x-ay)
is minimized. This is accomplished by first computing the Choleski decomposition of v:
v=LL^T.
One then solves for y in the equation
L^{-1}ay=L^{-1}x.
This is accomplished by means of a singular-value decomposition of L^{-1} a.
The resulting y then satisfies
x=ay+e,
where the entries of e are the residuals.
glssoln
returns a list of two named components:
coeff
is y as above.
residuals
is e as above.
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