Stochastic processes / Sheldon M. Ross
Tipo de material: TextoSeries Probability and mathematical statisticsDetalles de publicación: [s.l.] : John Wiley & Sons, 1996 Edición: 2nd ed.Descripción: XV, 510 p. ; 25 cmISBN: 0-471-12062-6Tema(s): Procesos estocásticosResumen: A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.Tipo de ítem | Biblioteca de origen | Signatura | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | Bibliografía recomendada |
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Manuales | 02. BIBLIOTECA CAMPUS PUERTO REAL | 519.216/ROS/sto (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3742087436 |
PROCESOS ESTOCÁSTICOS Y SERIES TEMPORALES GRADO EN MATEMÁTICAS Asignatura actualizada 2022-2023 |
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Monografías | 07. BIBLIOTECA CIENCIAS SOCIALES Y JURÍDICAS | 519.216/ROS/sto (Navegar estantería(Abre debajo)) | Texto completo | Prestado | 31/01/2025 | 3742186159 |
MODELIZACION. PROCESOS ESTOCASTICOS (UCA) MÁSTER EN MATEMÁTICAS Asignatura actualizada 2023-2024 |
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A nonmeasure theoretic introduction to stochastic processes. Considers its diverse range of applications and provides readers with probabilistic intuition and insight in thinking about problems. This revised edition contains additional material on compound Poisson random variables including an identity which can be used to efficiently compute moments; a new chapter on Poisson approximations; and coverage of the mean time spent in transient states as well as examples relating to the Gibb's sampler, the Metropolis algorithm and mean cover time in star graphs. Numerous exercises and problems have been added throughout the text.
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