Foster's Criterion Research Articles

Necessary and sufficient conditions for non-singular invariant probability measures for Feller Markov chains

In this paper, we present necessary and sufficient conditions for the existence of a non-singular invariant probability measure for a Feller Markov chain taking values on a locally compact separable metric space. The necessary and sufficient condition is written in terms of the Foster's criterion with an extra requirement. Furthermore, we extend an assumption recently presented by the authors Costa and Dufour, Statist. Probab. Lett. 50 (3) (2000) 13–21, named T2 condition, which generalizes T-chain and irreducibility assumptions for Feller Markov chains on a locally compact separable metric space, and show that under this assumption the extra requirement on the Foster's criterion can be eliminated.

Invariant probability measures for a class of Feller Markov chains

In this paper we consider a Markov chain defined on a locally compact separable metric space which satisfies the Feller property. We introduce a new assumption which generalizes T-chain and irreducibility assumptions, well known in the literature of Markov chains. Under this new assumption, the Foster's criterion is shown to be equivalent to the existence of an invariant probability measure for Feller–Markov chains, which is also equivalent to the existence of a non-singular invariant probability measure.

Work-modulated queues with applications to storage processes

We study two FIFO single-server queueing models in which both the arrival and service processes are modulated by the amount of work in the system. In the first model, the nth customer's service time, Sn , depends upon their delay, Dn , in a general Markovian way and the arrival process is a non-stationary Poisson process (NSPP) modulated by work, that is, with an intensity that is a general deterministic function g of work in system V(t). Some examples are provided. In our second model, the arrivals once again form a work-modulated NSPP, but, each customer brings a job consisting of an amount of work to be processed that is i.i.d. and the service rate is a general deterministic function r of work. This model can be viewed as a storage (dam) model (Brockwell et al. (1982)), but, unlike previous related literature, (where the input is assumed work-independent and stationary), we allow a work-modulated NSPP. Our approach involves an elementary use of Foster's criterion (via Tweedie (1976)) and in addition to obtaining new results, we obtain new and simplified proofs of stability for some known models. Using further criteria of Tweedie, we establish sufficient conditions for the steady-state distribution of customer delay and sojourn time to have finite moments.

Work-modulated queues with applications to storage processes

We study two FIFO single-server queueing models in which both the arrival and service processes are modulated by the amount of work in the system. In the first model, the nth customer's service time, Sn, depends upon their delay, Dn, in a general Markovian way and the arrival process is a non-stationary Poisson process (NSPP) modulated by work, that is, with an intensity that is a general deterministic function g of work in system V(t). Some examples are provided. In our second model, the arrivals once again form a work-modulated NSPP, but, each customer brings a job consisting of an amount of work to be processed that is i.i.d. and the service rate is a general deterministic function r of work. This model can be viewed as a storage (dam) model (Brockwell et al. (1982)), but, unlike previous related literature, (where the input is assumed work-independent and stationary), we allow a work-modulated NSPP. Our approach involves an elementary use of Foster's criterion (via Tweedie (1976)) and in addition to obtaining new results, we obtain new and simplified proofs of stability for some known models. Using further criteria of Tweedie, we establish sufficient conditions for the steady-state distribution of customer delay and sojourn time to have finite moments.

Invariant measures for Markov chains with no irreducibility assumptions

Foster's criterion for positive recurrence of irreducible countable space Markov chains is one of the oldest tools in applied probability theory. In various papers in JAP and AAP it has been shown that, under extensions of irreducibility such as ϕ -irreducibility, analogues of and generalizations of Foster's criterion give conditions for the existence of an invariant measure π for general space chains, and for π to have a finite f-moment ∫π (dy)f(y), where f is a general function. In the case f ≡ 1 these cover the question of finiteness of π itself. In this paper we show that the same conditions imply the same conclusions without any irreducibility assumptions; Foster's criterion forces sufficient and appropriate regularity on the space automatically. The proofs involve detailed consideration of the structure of the minimal subinvariant measures of the chain. The results are applied to random coefficient autoregressive processes in order to illustrate the need to remove irreducibility conditions if possible.

Invariant measures for Markov chains with no irreducibility assumptions

Foster's criterion for positive recurrence of irreducible countable space Markov chains is one of the oldest tools in applied probability theory. In various papers in JAP and AAP it has been shown that, under extensions of irreducibility such as ϕ -irreducibility, analogues of and generalizations of Foster's criterion give conditions for the existence of an invariant measure π for general space chains, and for π to have a finite f-moment ∫π (dy)f(y), where f is a general function. In the case f ≡ 1 these cover the question of finiteness of π itself.In this paper we show that the same conditions imply the same conclusions without any irreducibility assumptions; Foster's criterion forces sufficient and appropriate regularity on the space automatically. The proofs involve detailed consideration of the structure of the minimal subinvariant measures of the chain.The results are applied to random coefficient autoregressive processes in order to illustrate the need to remove irreducibility conditions if possible.

On the equivalence of certain Markov chains

It is shown that an irreducible and aperiodic Markov chain can be altered preserving irreducibility without altering the nature of the chain in the sense that, the modified chain is transient (recurrent) if and only if the original chain is transient (recurrent). Furthermore, it is shown by means of a counterexample that ergodicity (null-recurrence) is not preserved. An interesting application of this result is a simple proof of Pakes's generalization of Foster's criterion for a chain to be recurrent.

On the equivalence of certain Markov chains

It is shown that an irreducible and aperiodic Markov chain can be altered preserving irreducibility without altering the nature of the chain in the sense that, the modified chain is transient (recurrent) if and only if the original chain is transient (recurrent). Furthermore, it is shown by means of a counterexample that ergodicity (null-recurrence) is not preserved.An interesting application of this result is a simple proof of Pakes's generalization of Foster's criterion for a chain to be recurrent.