Quasi-stationary distributions for reducible absorbing Markov chains in discrete time

We consider discrete-time Markov chains with one coffin state and a finite set $S$ of transient states, and are interested in the limiting behaviour of such a chain as time $n \to \infty,$ conditional on survival up to $n$. It is known that, when $S$ is irreducible, the limiting conditional distribution of the chain equals the (unique) quasi-stationary distribution of the chain, while the latter is the (unique) $\rho$-invariant distribution for the one-step transition probability matrix of the (sub)Markov chain on $S,$ $\rho$ being the Perron-Frobenius eigenvalue of this matrix. Addressing similar issues in a setting in which $S$ may be reducible, we identify all quasi-stationary distributions and obtain a necessary and sufficient condition for one of them to be the unique $\rho$-invariant distribution. We also reveal conditions under which the limiting conditional distribution equals the $\rho$-invariant distribution if it is unique. We conclude with some examples.

[1]  Hans Schneider,et al.  The influence of the marked reduced graph of a nonnegative matrix on the Jordan form and on related properties: A survey , 1986 .

[2]  H. Victory On Nonnegative Solutions of Matrix Equations , 1985 .

[3]  O. Aalen,et al.  Understanding the shape of the hazard rate: A proce ss point of view , 2002 .

[4]  E. Seneta Non-negative Matrices and Markov Chains , 2008 .

[5]  H. Schneider The Elementary Divisors, Associated with 0, of a Singular M-matrix , 1956, Proceedings of the Edinburgh Mathematical Society.

[6]  Carl D. Meyer,et al.  Matrix Analysis and Applied Linear Algebra , 2000 .

[7]  On the maximum eigenvalue of a reducible non-negative real matrix , 1973 .

[8]  B. Lindqvist Asymptotic properties of powers of nonnegative matrices, with applications , 1989 .

[9]  E. Seneta,et al.  On Quasi-Stationary distributions in absorbing discrete-time finite Markov chains , 1965, Journal of Applied Probability.

[10]  D. Carlson A Note on M-Matrix Equations , 1963 .

[11]  Valerie Isham,et al.  Non‐Negative Matrices and Markov Chains , 1983 .

[12]  Odd O. Aalen,et al.  A LOOK BEHIND SURVIVAL DATA: UNDERLYING PROCESSES AND QUASI-STATIONARITY , 2003 .

[13]  Milton C Weinstein,et al.  Heart failure disease management programs: a cost-effectiveness analysis. , 2008, American heart journal.

[14]  Philip K. Pollett,et al.  Survival in a quasi-death process , 2008 .

[15]  David Steinsaltz,et al.  Markov mortality models: implications of quasistationarity and varying initial distributions. , 2004, Theoretical population biology.