Mercurial > hg > camir-aes2014
annotate toolboxes/FullBNT-1.0.7/KPMstats/est_transmat.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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rev | line source |
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wolffd@0 | 1 function [A,C] = est_transmat(seq) |
wolffd@0 | 2 % ESTIMATE_TRANSMAT Max likelihood of a Markov chain transition matrix |
wolffd@0 | 3 % [A,C] = estimate_transmat(seq) |
wolffd@0 | 4 % |
wolffd@0 | 5 % seq is a vector of positive integers |
wolffd@0 | 6 % |
wolffd@0 | 7 % e.g., seq = [1 2 1 2 3], C(1,2)=2, C(2,1)=1, C(2,3)=1, so |
wolffd@0 | 8 % A(1,:)=[0 1 0], A(2,:) = [0.5 0 0.5], |
wolffd@0 | 9 % all other entries are 0 |
wolffd@0 | 10 |
wolffd@0 | 11 % Use a trick with sparse matrices to count the number of each transition. |
wolffd@0 | 12 % From http://www.mathworks.com/company/newsletter/may03/dna.shtml |
wolffd@0 | 13 |
wolffd@0 | 14 C = full(sparse(seq(1:end-1), seq(2:end),1)); |
wolffd@0 | 15 A = mk_stochastic(C); |