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Books on the topic 'Stochastic modelling theory'

Author: Grafiati

Published: 19 February 2023

Last updated: 20 February 2023

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1

B, Vinter R., ed. Stochastic modelling and control. London: Chapman and Hall, 1985.

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2

India) International Conference on Stochastic Modelling (2002 Cochin. Advances in stochastic modelling. Edited by Artalejo J. R, Krishnamoorthy A, and International Workshop on Retrial Queues (4th : 2002 : Cochin, India). Neshanic Station, NJ: Notable Publications, 2002.

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3

Wolff, Ronald W. Stochastic modelling and the theory of queues. London: Prentice-Hall, 1989.

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4

Desai, Uday B. Modelling and Application of Stochastic Processes. Boston, MA: Springer US, 1986.

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5

Wang, Hong. Bounded Dynamic Stochastic Systems: Modelling and Control. London: Springer London, 2000.

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6

Turbulence in fluids: Stochastic and numerical modelling. 2nd ed. Dordrecht: Kluwer Academic Publishers, 1990.

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7

Lesieur, Marcel. Turbulence in Fluids: Stochastic and numerical modelling. Dordrecht: Springer Netherlands, 1987.

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8

Turbulence in fluids: Stochastic and numerical modelling. Dordrecht: M. Nijhoff, 1987.

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9

Janssen, Jacques. Advances in Stochastic Modelling and Data Analysis. Dordrecht: Springer Netherlands, 1995.

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10

Tijms, Henk C. Stochastic Modeling and Analysis: A Computational Approach. Chichester, New York, USA: John Wiley & Sons Ltd., 1986.

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11

Probability, stochastic processes, and queueing theory: The mathematics of computer performance modelling. New York: Springer-Verlag, 1995.

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12

Dynamic feature space modelling, filtering, and self-tuning control of stochastic systems: A systems approach with economic and social applications. Berlin: Springer-Verlag, 1985.

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13

Stochastic calculus for finance. New York: Springer, 2004.

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14

Stochastic Networks and Queues (Stochastic Modelling and Applied Probability). Springer, 2003.

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15

1945-, Gerencsér L., and Caines Peter E. 1945-, eds. Topics in stochastic systems: Modelling, estimation, and adaptive control. Berlin: Springer-Verlag, 1991.

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16

Yong, Jiongmin, and Xun Yu Zhou. Stochastic Controls: Hamiltonian Systems and HJB Equations (Stochastic Modelling and Applied Probability). Springer, 1999.

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17

Fleming, Wendell H., and H. M. Soner. Controlled Markov Processes and Viscosity Solutions (Stochastic Modelling and Applied Probability). Springer, 2005.

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18

Fleming, Wendell H., and Halil Mete Soner. Controlled Markov Processes and Viscosity Solutions (Stochastic Modelling and Applied Probability Book 25). Springer, 2006.

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19

Wave Propagation and Time Reversal in Randomly Layered Media (Stochastic Modelling and Applied Probability). Springer, 2007.

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20

Morale, Daniela. Math Everywhere: Deterministic and Stochastic Modelling in Biomedicine, Economics and Industry. Springer London, Limited, 2007.

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21

Hernandez-Lerma, Onesimo, and Xianping Guo. Continuous-Time Markov Decision Processes: Theory and Applications (Stochastic Modelling and Applied Probability Book 62). Springer, 2009.

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22

Otter, Pieter W. Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems: A Systems Approach with Economic and Social Applications. Brand: Springer, 1985.

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23

Otter, Pieter W. Dynamic Feature Space Modelling, Filtering and Self-Tuning Control of Stochastic Systems: A Systems Approach with Economic and Social Applications. Springer London, Limited, 2012.

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24

G, Aletti, Burger Martin, Micheletti P. A. 1951-, Morale Daniela, and Capasso Vincenzo 1945-, eds. Math everywhere: Deterministic and stochastic modelling in biomedicine, economics and industry ; dedicated to the 60th birthday of Vincenzo Capasso. Berlin: Springer, 2007.

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25

Chambers, Robert G. Competitive Agents in Certain and Uncertain Markets. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190063016.001.0001.

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Abstract:

This book uses concepts from optimization theory to develop an integrated analytic framework for treating consumer, producer, and market equilibrium analyses as special cases of a generic optimization problem. The same framework applies to both stochastic and non-stochastic decision settings, so that the latter is recognized as an (important) special case of the former. The analytic techniques are borrowed from convex analysis and variational analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. The book shows how virtually identical conjugate analyses form the basis for modeling economic behavior in each of the areas studied. The basic analytic concepts are borrowed from convex analysis. Special emphasis is given to generalized notions of differentiability, conjugacy theory, and Fenchel's Duality Theorem. It is demonstrated how virtually identical conjugate analyses form the basis for modelling economic behaviour in each of the areas studied.

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26

Fernholz, E. Robert. Stochastic Portfolio Theory. Springer London, Limited, 2013.

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27

Stochastic Portfolio Theory. Springer, 2002.

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28

Fernholz, E. Robert. Stochastic Portfolio Theory. Springer, 2010.

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29

The Coale-McNeil Model: Theory, Generalization and Application. Purdue University Press, 2000.

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