Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/KPMstats/mc_stat_distrib.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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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]; | |
25 | |
26 |