Books on the topic 'Simulation de processus distribués'

Shedler, G. S. Regenerative stochastic simulation. Boston: Academic Press, 1993.

Plenge, Waagepetersen Rasmus, ed. Statistical inference and simulation for spatial point processes. Boca Raton, Fla: Chapman & Hall/CRC, 2004.

Hay, Lee Loo, ed. Stochastic simulation optimization: An optimal computing budget allocation. New Jersey: World Scientific, 2011.

Benchekroun, Tahar Hakim. Modélisation et simulation des processus intentionnels d'interlocution: Application à la conception d'un système d'aide à la communication multi-agents. Lille: A.N.R.T, Université de Lille III, 1994.

Heermann, Dieter W. Computer simulation methods in theoretical physics. 2nd ed. Berlin: Springer-Verlag, 1990.

Heermann, Dieter W. Computer simulation methods in theoretical physics. 2nd ed. Berlin: Springer-Verlag, 1990.

Dennis, Terry L. Microcomputer models for management decision-making: Software and text. 3rd ed. Minneapolis: West Pub. Co., 1993.

Dennis, Terry L. Microcomputer models for management decision-making: Software and text. St. Paul, MN: West Pub. Co., 1986.

R, Gilks W., Richardson S, and Spiegelhalter D. J, eds. Markov chain Monte Carlo in practice. London: Chapman & Hall, 1996.

R, Gilks W., Richardson S, and Spiegelhalter D. J, eds. Markov chain Monte Carlo in practice. Boca Raton, Fla: Chapman & Hall, 1998.

R, Uttal William, ed. The Swimmer: An integrated computational model of a perceptual-motor system. Hillsdale, N.J: L. Erlbaum, 1992.

m, Michel Benai. Promenade ale atoire: Chai nes de Markov et simulations ; martingales et strate gies. Palaiseau: E ditions de l'E cole polytechnique, 2004.

Cooper, Robert B. Introduction to queueing theory. 3rd ed. Washington, D.C: CEEPress Books, 1990.

Søren, Brunak, ed. Bioinformatics: The machine learning approach. 2nd ed. Cambridge, Mass: MIT Press, 2001.

Søren, Brunak, ed. Bioinformatics: The machine learning approach. Cambridge, Mass: MIT Press, 1998.

Schoutens, Wim. Lévy processes in finance: Pricing financial derivatives. Chichester, West Sussex: J. Wiley, 2003.

Canicas, Jean-François. Formalisation et simulation du processus de reconnaissance intermoléculaire. 1985.

COCHARD. Introduction Aux Proc Stoch Simulation: Introduction Aux Processus Stochastiques et a la Simulation. ISTE Editions Ltd., 2019.

Moller, Jesper, Rasmus Plenge Waagepetersen, and Jesper Møller. Statistical Inference and Simulation for Spatial Point Processes. Taylor & Francis Group, 2003.

Methodes et modeles de la recherche operationnelle (Collection Gestion : serie : politique generale, finance et marketing). Economica, 1998.

Computational Modeling of Vision: The Role of Combination (Optical Engineering, V. 62). CRC, 1999.

Introduction to stochastic search and optimization: Estimation, simulation, and control. Hoboken, N.J: J. Wiley, 2003.

Spall, James C. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control. Wiley & Sons, Incorporated, John, 2008.

Spall, James C. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control. Wiley & Sons, Incorporated, John, 2005.

Moller, Jesper, and Rasmus Plenge Waagepetersen. Statistical Inference and Simulation for Spatial Point Processes (Monographs on Statistics and Applied Probability). Chapman & Hall/CRC, 2003.

Maillardet, Robert, Andrew Robinson, and Owen Jones. Introduction to Scientific Programming and Simulation Using R. Taylor & Francis Group, 2014.

Maillardet, Robert, Andrew Robinson, and Owen Jones. Introduction to Scientific Programming and Simulation Using R. Taylor & Francis Group, 2009.

Jones, Owen, Robert Maillardet, and Andrew Robinson. Introduction to Scientific Programming and Simulation Using R. Taylor & Francis Group, 2014.

Garcia, Juan Martin. Modèles de Simulation Avec Dynamique des Systèmes : Applications de Modelisation en économie, écologie, Biologie, Gestion Opérationnelle et des Processus de Fabrication. Complexité: Concepts et Exercices. Independently Published, 2019.

Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences. Taylor & Francis Group, 2020.

Gramacy, Robert B. Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences. Taylor & Francis Group, 2020.

Gramacy, Robert B. Surrogates. Taylor & Francis Group, 2020.

Gramacy, Robert B. Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences. Taylor & Francis Group, 2020.

Gramacy, Robert B. Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences. Taylor & Francis Group, 2020.

Richardson, S., David Spiegelhalter, and W. R. Gilks. Markov Chain Monte Carlo in Practice. Taylor & Francis Group, 1995.

Richardson, S., David Spiegelhalter, and W. R. Gilks. Markov Chain Monte Carlo in Practice. Taylor & Francis Group, 1995.

Shepherd, Thomas, Gary Bradshaw, Sriram Dayanand, Robb Lovell, and William R. Uttal. Swimmer: An Integrated Computational Model of a Perceptual-Motor System. Taylor & Francis Group, 2014.

Shepherd, Thomas, Gary Bradshaw, Sriram Dayanand, Robb Lovell, and William R. Uttal. Swimmer: An Integrated Computational Model of a Perceptual-Motor System. Taylor & Francis Group, 2014.

Shepherd, Thomas, Gary Bradshaw, Sriram Dayanand, Robb Lovell, and William R. Uttal. Swimmer: An Integrated Computational Model of a Perceptual-Motor System. Taylor & Francis Group, 2016.

Shepherd, Thomas, Gary Bradshaw, Sriram Dayanand, Robb Lovell, Ramakrishna Kakarala, Kurt Skifsted, Greg Tupper, and William R. Uttal. The Swimmer: An Integrated Computational Model of A Perceptual-motor System (Scientific Psychology Series). Lawrence Erlbaum, 1992.

Kumar M., Dileep. 50 short case studies in business management. UUM Press, 2012. http://dx.doi.org/10.32890/9789670474243.

Handbook for Markov chain Monte Carlo. Boca Raton: Taylor & Francis, 2011.

Schoutens, Wim. Lévy Processes in Finance: Pricing Financial Derivatives. Wiley & Sons, Incorporated, John, 2003.