comparison toolboxes/FullBNT-1.0.7/KPMstats/mc_stat_distrib.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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-1:000000000000 0:e9a9cd732c1e
1 function pi = mc_stat_distrib(P)
2 % MC_STAT_DISTRIB Compute stationary distribution of a Markov chain
3 % function pi = mc_stat_distrib(P)
4 %
5 % Each row of P should sum to one; pi is a column vector
6
7 % Kevin Murphy, 16 Feb 2003
8
9 % The stationary distribution pi satisfies pi P = pi
10 % subject to sum_i pi(i) = 1, 0 <= pi(i) <= 1
11 % Hence
12 % (P' 0n (pi = (pi
13 % 1n 0) 1) 1)
14 % or P2 pi2 = pi2.
15 % Naively we can solve this using (P2 - I(n+1)) pi2 = 0(n+1)
16 % or P3 pi2 = 0(n+1), i.e., pi2 = P3 \ zeros(n+1,1)
17 % but this is singular (because of the sum-to-one constraint).
18 % Hence we replace the last row of P' with 1s instead of appending ones to create P2,
19 % and similarly for pi.
20
21 n = length(P);
22 P4 = P'-eye(n);
23 P4(end,:) = 1;
24 pi = P4 \ [zeros(n-1,1);1];
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