A Course in Stochastic Processes: Stochastic Models and Statistical Inference

Author:   Denis Bosq ,  Hung T. Nguyen
Publisher:   Springer
Edition:   Softcover reprint of hardcover 1st ed. 1996
Volume:   34
ISBN:  

9789048147137


Pages:   354
Publication Date:   09 December 2010
Format:   Paperback
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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A Course in Stochastic Processes: Stochastic Models and Statistical Inference


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Overview

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.

Full Product Details

Author:   Denis Bosq ,  Hung T. Nguyen
Publisher:   Springer
Imprint:   Springer
Edition:   Softcover reprint of hardcover 1st ed. 1996
Volume:   34
Dimensions:   Width: 17.00cm , Height: 1.90cm , Length: 24.40cm
Weight:   0.635kg
ISBN:  

9789048147137


ISBN 10:   9048147131
Pages:   354
Publication Date:   09 December 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

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.- A.l Extension of measures.- A.2 Product measures.- A.3 Some theorems on integrals.- B Banach and Hilbert Spaces.- B.l Definitions.- B.3 Hilbert spaces.- B.4 Fourier series.- B.5 Applications to probability theory.- List of Symbols.- Partial Solutions to Selected Exercises.

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