x = lscov(A,b,V)
x = lscov(A,b,V)
returns the vector x
that minimizes
(A
*x-b)'
*inv(V)
*(A
*x-b)
for the case in which length(b)
>
length(x)
. This is the over-determined least squares problem with covariance V
. V
is a square symmetric matrix with dimensions equal to length(b)
. The solution is found without inverting V
.
but this function computes the QR decomposition ofx
=
inv(A'
*inv(V)
*A)
*A'
*inv(V)
*b
A
and then modifies Q
by V
.
\
,nnls
,qr
(c) Copyright 1994 by The MathWorks, Inc.