Computing the Maximal Eigenvalue and Eigenvector of a Nonnegative Irreducible Matrix

1968 ◽  
Vol 5 (3) ◽  
pp. 470-474 ◽  
Author(s):  
C. A. Hall ◽  
T. A. Porsching
Keyword(s):  
Irreducible Matrix ◽  
Maximal Eigenvalue ◽  
Eigenvalue And Eigenvector ◽  
Nonnegative Irreducible Matrix

scholarly journals A Numerical Algorithm on the Computation of the Stationary Distribution of a Discrete Time Homogenous Finite Markov Chain

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Di Zhao ◽  
Hongyi Li ◽  
Donglin Su
Keyword(s):  
Markov Chain ◽  
Stationary Distribution ◽  
Discrete Time ◽  
Transition Matrix ◽  
Stochastic Matrix ◽  
Nonnegative Matrix ◽  
Homogeneous Markov Chain ◽  
Irreducible Matrix ◽  
Nonnegative Irreducible Matrix ◽  
Perron Vector

The transition matrix, which characterizes a discrete time homogeneous Markov chain, is a stochastic matrix. A stochastic matrix is a special nonnegative matrix with each row summing up to 1. In this paper, we focus on the computation of the stationary distribution of a transition matrix from the viewpoint of the Perron vector of a nonnegative matrix, based on which an algorithm for the stationary distribution is proposed. The algorithm can also be used to compute the Perron root and the corresponding Perron vector of any nonnegative irreducible matrix. Furthermore, a numerical example is given to demonstrate the validity of the algorithm.

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