Duality for a class of continuous-time reversible Markov models
Using a conditional probability structure we build transition probabilities that drive appealing classes of reversible Markov processes. The mechanism used in such a construction allows to find a dual Markov process. This kind of duality is then used to compute the predictor operator of one process...
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| Published in | Statistics (Berlin, DDR) Vol. 55; no. 1; pp. 231 - 242 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Abingdon
Taylor & Francis
02.01.2021
Taylor & Francis Ltd |
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| Abstract | Using a conditional probability structure we build transition probabilities that drive appealing classes of reversible Markov processes. The mechanism used in such a construction allows to find a dual Markov process. This kind of duality is then used to compute the predictor operator of one process via its dual. In particular, we identify the dual of some non-conjugate models, namely the
queue model and a simple birth, death and immigration process. Such duals ensure that the computation of the predictor operators can be done via finite sums. |
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| AbstractList | Using a conditional probability structure we build transition probabilities that drive appealing classes of reversible Markov processes. The mechanism used in such a construction allows to find a dual Markov process. This kind of duality is then used to compute the predictor operator of one process via its dual. In particular, we identify the dual of some non-conjugate models, namely the
queue model and a simple birth, death and immigration process. Such duals ensure that the computation of the predictor operators can be done via finite sums. Using a conditional probability structure we build transition probabilities that drive appealing classes of reversible Markov processes. The mechanism used in such a construction allows to find a dual Markov process. This kind of duality is then used to compute the predictor operator of one process via its dual. In particular, we identify the dual of some non-conjugate models, namely the queue model and a simple birth, death and immigration process. Such duals ensure that the computation of the predictor operators can be done via finite sums. |
| Author | Palma, Freddy Mena, Ramsés H. |
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| Cites_doi | 10.1016/j.spl.2019.04.004 10.1214/12-PS206 10.3150/13-BEJ548 10.1214/aop/1176990628 10.1111/1467-9469.00311 10.1017/S0305004100027638 10.1007/978-3-662-00031-1 10.1214/16-EJS1194 10.1090/gsm/113 10.1017/CBO9781139344203 10.2307/3318443 10.2307/1911242 10.1214/105051606000000600 |
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| Copyright | 2021 Informa UK Limited, trading as Taylor & Francis Group 2021 2021 Informa UK Limited, trading as Taylor & Francis Group |
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| Snippet | Using a conditional probability structure we build transition probabilities that drive appealing classes of reversible Markov processes. The mechanism used in... |
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| SubjectTerms | Conditional probability Duality for Markov process Markov chains Markov processes reversible Markov process theory of queues Transition probabilities |
| Title | Duality for a class of continuous-time reversible Markov models |
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