How to compute stationary distribution for martrix with more than 1 closed class

AI Thread Summary
The discussion focuses on computing stationary distributions for a matrix with multiple closed classes. The matrix provided has an absorbing state, specifically the third state, which simplifies the analysis. To find the stationary distributions, it is recommended to convert the matrix into canonical form and apply standard methods. Solving the eigenvector equation xA=x is suggested, as the matrix contains two linearly independent eigenvectors corresponding to the closed classes. The final stationary distributions can be determined by ensuring positivity and that the values sum to one.
sam48
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Hi,

Thank you in advance if anyone can answer this question.

How any stationary distributions exists in below matrix and what are the value

[
.5 0 0 .5
.25 .5 .25 0
0 0 1 0
1/6 0 0 5/6
]

Any information regarding how to compute stationary distribution in a martrix with more than 1 closed class would be appreciated.
regards,
 
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Your chain has an absorbing state (the third state, since the 3,3 entry is 1). Write this matrix in canonical form and analyze it with the standard methods.
 


One way is just to solve the eigenvector equation xA=x - since your example has 2 closed classes (the other being {1,4}), there will be two LI eigenvectors. Positivity and summation to 1 will tell you which linear combinations are valid.
 
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