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Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
classmarkov
recurrent and transient classes of Markov matrix
Calling Sequence
[perm,rec,tr,indsRec,indsT]=classmarkov(M)
Arguments
- M
real N x N Markov matrix. Sum of entries in each row should add to one.
- perm
integer permutation vector.
- rec, tr
integer vector, number (number of states in each recurrent classes, number of transient states).
- indsRec,indsT
integer vectors. (Indexes of recurrent and transient states).
Description
Returns a permutation vector perm
such that
M(perm,perm) = [M11 0 0 0 0 0] [0 M22 0 0 0] [0 0 M33 0] [ ... ] [0 0 Mrr 0] [* * * Q]
Each Mii
is a Markov matrix of dimension rec(i) i=1,..,r
.
Q
is sub-Markov matrix of dimension tr
.
States 1 to sum(rec) are recurrent and states from r+1 to n
are transient.
One has perm=[indsRec,indsT]
where indsRec is a vector of size sum(rec)
and indsT is a vector of size tr.
Examples
//P has two recurrent classes (with 2 and 1 states) 2 transient states P=genmarkov([2,1],2,'perm') [perm,rec,tr,indsRec,indsT]=classmarkov(P); P(perm,perm)
See Also
- genmarkov — generates random markov matrix with recurrent and transient classes
- eigenmarkov — normalized left and right Markov eigenvectors
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