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Linear least squares, condition number |
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| Aug20-08, 02:35 PM | #1 |
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Linear least squares, condition number
Hi,
I am trying to learn some numerical algebra. Now I don't understand the following. I'm finding the solution to the Linear Least Squares problem [tex]min||A\lambda-y||_{2}[/tex], which turns out to be (1,1). I did this by doing a QR factorization using Givens rotations. with: [latex] A= \[ \left( \begin{array}{ccc} 1 & 1\\ 1 & 1.0001\\ 1 & 1.0001\end{array} \right)\][/latex] and [latex] y= \[ \left( \begin{array}{ccc} 2\\ 0.0001\\ 4.0001\end{array} \right)\] [/latex] Now, I have a Octave (matlab clone) program that does the same calculation. As the condition number of the matrix A is very large (4.2429e+004) (found by applying Octave's cond() function on A), I expect the solution to be at least not exact. Yet the Octave program gives the exact solution (1,1), at least, as far as I can see (6 digit accuracy I think), that is. Can someone explain this? Also, should one consider the condition number of the matrix A when considering the condition of the Linear Least Squares problem, or the condition number of the Matrix A|y? (The condition number of the latter is even bigger so my first question holds in any case). Thank you :) |
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