Large sample inference from G/G/1 retrial queues
We consider a general G/G/1 retrial queue where retrials can be non Markovian. We obtain asymptotically Gaussian consistent estimators for an unknown k-dimensional parameter assuming that the distribution functions of the variables involved are known. We consider distinct levels of information which...
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 1994 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/64105 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/64105 |
| Access Level: | acceso abierto |
| Palabra clave: | G/G/1 retrial queue Maximun likelihood estimation General retrials Matemáticas (Matemáticas) 12 Matemáticas |
| Sumario: | We consider a general G/G/1 retrial queue where retrials can be non Markovian. We obtain asymptotically Gaussian consistent estimators for an unknown k-dimensional parameter assuming that the distribution functions of the variables involved are known. We consider distinct levels of information which can be interpreted as different disciplines of service. We analyze the problem of impatient customers in a G/G/1 queue as a particular case. We also give some explicit estimators for Markovian queues. |
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