Results 231 to 240 of about 123,412 (280)

Comparing Semi-Markov Processes

Mathematics of Operations Research, 1980
Sufficient conditions are found for two semi-Markov processes to be stochastically ordered, i.e., for which two new semi-Markov processes can be constructed on a common probability space so that the new processes individually have the same distributions as the original processes and every sample path of the first new process lies below the ...
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Monotonicity in Generalized Semi-Markov Processes

Mathematics of Operations Research, 1992
We establish stochastic monotonicity of the event epoch sequences of generalized semi-Markov processes through the structure of the generalized semi-Markov schemes on which they are based. Our main condition states, roughly, that the occurrence of more events in the short run never leads to the activation of less events in the long run.
Paul Glasserman, David D. Yao
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Continuity of Generalized Semi-Markov Processes

Mathematics of Operations Research, 1980
It is shown that sequences of generalized semi-Markov processes converge in the sense of weak convergence of random functions if associated sequences of defining elements (initial distributions, transition functions and clock time distributions) converge.
Ward Whitt
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On reversible semi-Markov processes

Operations Research Letters, 1994
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Using Semi-Markov Chains to Solve Semi-Markov Processes

Methodology and Computing in Applied Probability, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Bei, Maya, Brenda Ivette Garcia, Limnios, Nikolaos   +2 more
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A characterization for mixtures of semi-Markov processes

Statistics & Probability Letters, 2002
A stepped right-continuous random process with a countable space of states \(I\) is considerd. It can be represented by the random sequence \((\sigma_j, \xi_j)_1^\infty\), where \(\sigma_j\) is the \(j\)th jump time, and \(\xi_j\in I\) is the value of the process at time \(\sigma_j\). Let \(\nu_{im}\) be the \(m\)th hitting time of the state \(i\in I\),
EPIFANI, ILENIA, S. Fortini, LADELLI, LUCIA MARIA   +2 more
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Functions of Semi-Markov Processes

SIAM Journal on Applied Mathematics, 1971
A necessary and sufficient condition is presented under which a function of a semi-Markov process is again a semi-Markov process with transition probabilities which do not depend on the initial distribution of the original process. This result is a generalization of a known result for Markov processes.
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Semi-Markov Processes

2001
Let Q(x,A,t), x ∈ E, A ∈ e,t ∈ IR+, be a semi-Markov kernel on (E,e) and let (J n ,S n )n∈N and (J n ,X n )n∈N be, respectively, the associated MRP and the (J-X)-process (see Section 2.2).
N. Limnios, G. Oprişan
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Regenerative generalized semi-markov processes

Communications in Statistics. Stochastic Models, 1987
The authors deal with a generalized semi-Markov process, which permits formal specification of some non-Markovian simulation models.
Haas, Peter J., Shedler, Gerald S.
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