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Overflow asymptotics for large communication systems with general Markov fluid sources
Mandjes, Michel - 1996
Persistent link: https://www.econbiz.de/10000930033
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Importance sampling of buffer overflows in batch-arrival queues
Mandjes, Michel - 1995
Persistent link: https://www.econbiz.de/10000905139
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Bandwith-sharing networks under a diffusion scaling
Ayesta, Urtzi; Mandjes, Michel - 2009
Persistent link: https://www.econbiz.de/10003865982
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Tail distribution of the maximum of correlated Gaussian random variables
Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...
Persistent link: https://www.econbiz.de/10011431354
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Fast simulation of Markov modulated fluid models
Ridder, Ad - 1995
Persistent link: https://www.econbiz.de/10000905138
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Finding the conjugate of Markov fluid processes
Mandjes, Michel - 1995
Persistent link: https://www.econbiz.de/10000905140
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Fast simulation of a queue fed by a superposition of many (heavy-tailed) sources
Boots, Nam Kyoo; Mandjes, Michel - 2001
Persistent link: https://www.econbiz.de/10001585023
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The shape of the loss curve and the impact of long-range dependence on network performance
Mandjes, Michel; Boots, Nam Kyoo - 2001
Persistent link: https://www.econbiz.de/10001585028
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Tail Distribution of the Maximum of Correlated Gaussian Random Variables
Botev, Zdravko - 2015
In this article we consider the efficient estimation of the tail distribution of the maximum of correlated normal random variables. We show that the currently recommended Monte Carlo estimator has difficulties in quantifying its precision, because its sample variance estimator is an inefficient...
Persistent link: https://www.econbiz.de/10013010233
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Affine storage and insurance risk models
Boxma, Onno; Mandjes, Michel - In: Mathematics of operations research 46 (2021) 4, pp. 1282-1302
Persistent link: https://www.econbiz.de/10012796641