A Course in Stochastic Processes: Stochastic Models and Statistical Inference by Denis BosqA Course in Stochastic Processes: Stochastic Models and Statistical Inference by Denis Bosq

A Course in Stochastic Processes: Stochastic Models and Statistical Inference

byDenis Bosq

Paperback | December 9, 2010

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This volume is an introduction to stochastic processes and their statistics. Basic stochastic processes are developed from real world situations to the need for generating mathematical models, while at the same time students learn to apply theoretical models. The lessons cover basic stochastic processes such as Poisson processes, Markov chains, random walks, renewal theory, queuing theory, ARMA models, martingales, Brownian motion and diffusion processes. The statistical topics treated include the basic aspects of statistics of point processes, stationary processes and diffusion processes. Audience: This textbook will be useful for one-semester courses at graduate level to students of mathematics, statistics, computer science, electrical and industrial engineering and economics.
Title:A Course in Stochastic Processes: Stochastic Models and Statistical InferenceFormat:PaperbackDimensions:364 pages, 9.61 × 6.69 × 0.03 inPublished:December 9, 2010Publisher:Springer NetherlandsLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9048147131

ISBN - 13:9789048147137

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Table of Contents

Preface. 1. Basic Probability Background. 2. Modeling Random Phenomena. 3. Discrete-Time Markov Chains. 4. Poisson Processes. 5. Continuous-Time Markov Chains. 6. Random Walks. 7. Renewal Theory. 8. Queueing Theory. 9. Stationary Processes. 10. ARMA model. 11. Discrete-Time Martingales. 12. Brownian Motion and Diffusion Processes. 13. Statistics for Poisson Processes. 14. Statistics of Discrete-Time Stationary Processes. 15. Statistics of Diffusion Processes. A. Measure and Integration. B. Banach and Hilbert Spaces. List of Symbols. Bibliography. Partial Solutions to Selected Exercises. Index.