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Unformatted text preview: L ) with x i = Px i1 , so x i = P i x (or the same equations with P replaced by L ). In each case we get a steady state given by an eigenvector of the matrix. For the cases that occur in the applications the matrix P can be diagonalized; resp. we only need the positive eigenvalue, and we determine the steady state (resp. rate). Finally, we observe that the material of 4.4 follows directly from our work on eigenvalues, eigenvectors and eigenspaces....
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 Spring '08
 Dodson
 Markov Chains

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