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MARKOV STUDY P,L
where P is a matrix file of transition probabilities determines the
class structure of the Markov chain and gives the results from the
edit line L onwards as shown in the following example:
MATRIX P
///  T1  T2  T3  T4  T5
T1   0.4 0   0   0   0.6
T2   0.9 0   0   0.1 0
T3   0   0   0.2 0.8 0
T4   0   0   0.8 0.2 0
T5   0.7 0   0   0   0.3

MAT SAVE P
MARKOV STUDY P,CUR+1
Structure of Markov chain P of 5 states:
Class structure saved in matrix file MCLASS.M
2 recurrent classes of states:
1 (2): T1 T5
2 (2): T3 T4
1 transient state:
 T2

By default the results are obtained by finding the transitive closure
of the digraph determined by P.
By using the specification SVD=1 the same task is accomplished by
computing the singular value decomposition of I-P. Then also the
steady-state probabilities for each recurrent classes are calculated
and given as the second column of matrix MCLASS.M
In the above example this gives

LOADM MCLASS.M,(C7),CUR+1
Class_structure_of_P_(Transient_states=0)
           Class    Prob
T1             1 0.53846
T2             0 0.00000
T3             2 0.50000
T4             2 0.50000
T5             1 0.46154


   M = More information on Markov chains