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1996 | Buch

A Course in Stochastic Processes

Stochastic Models and Statistical Inference

verfasst von: Denis Bosq, Hung T. Nguyen

Verlag: Springer Netherlands

Buchreihe : Theory and Decision Library

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SUCHEN

Über dieses Buch

This text is an Elementary Introduction to Stochastic Processes in discrete and continuous time with an initiation of the statistical inference. The material is standard and classical for a first course in Stochastic Processes at the senior/graduate level (lessons 1-12). To provide students with a view of statistics of stochastic processes, three lessons (13-15) were added. These lessons can be either optional or serve as an introduction to statistical inference with dependent observations. Several points of this text need to be elaborated, (1) The pedagogy is somewhat obvious. Since this text is designed for a one semester course, each lesson can be covered in one week or so. Having in mind a mixed audience of students from different departments (Math­ ematics, Statistics, Economics, Engineering, etc.) we have presented the material in each lesson in the most simple way, with emphasis on moti­ vation of concepts, aspects of applications and computational procedures. Basically, we try to explain to beginners questions such as "What is the topic in this lesson?" "Why this topic?", "How to study this topic math­ ematically?". The exercises at the end of each lesson will deepen the stu­ dents' understanding of the material, and test their ability to carry out basic computations. Exercises with an asterisk are optional (difficult) and might not be suitable for homework, but should provide food for thought.

Inhaltsverzeichnis

Frontmatter
Lesson 1. Basic Probability Background
Abstract
This Lesson is a review of basic concepts in probability theory needed for this Text. The notation in this Lesson will be used throughout the Text unless otherwise stated. We emphasize computational aspects. The Appendix at the end of this Text contains additional topics.
Denis Bosq, Hung T. Nguyen
Lesson 2. Modeling Random Phenomena
Abstract
In this Lesson, we motivate the use of the concept of Stochastic Processes as a means to model random phenomena. It is emphasized that the analysis of random phenomena in terms of stochastic processes relies heavily on the mathematical theory of probability.
Denis Bosq, Hung T. Nguyen
Lesson 3. Discrete — Time Markov Chains
Abstract
This Lesson is devoted to detailed studies of an important class of stochastic processes whose time-dependent structures are simple but general enough to model a variety of practical random phenomena.
Denis Bosq, Hung T. Nguyen
Lesson 4. Poisson Processes
Abstract
This Lesson is devoted entirely to an important class of continuous-time Markov chains, the Poisson processes. This Lesson also serves as an introduction to continuous-time Markov chains where the general theory will be treated in Lesson 5.
Denis Bosq, Hung T. Nguyen
Lesson 5. Continuous — Time Markov Chains
Abstract
Poisson processes in Lesson 4 are examples of continuous-time stochastic processes (with discrete state spaces) having the Markov property in the continuous-time setting. In this Lesson, we discuss the probabilistic structure and some computational aspects of such processes with emphasis on Birth and Death chains.
Denis Bosq, Hung T. Nguyen
Lesson 6. Random Walks
Abstract
In this Lesson, we study a special class of discrete-time Markov chains known as random walks. Because of their special features, these stochastic processes deserve a Lesson in their own right.
Denis Bosq, Hung T. Nguyen
Lesson 7. Renewal Theory
Abstract
This Lesson is devoted to the study of a class of random walks whose steps are non-negative. With the interpretation of renewals, these stochastic processes model many random phenomena of interest. Renewal theory provides tools for the analysis of such processes.
Denis Bosq, Hung T. Nguyen
Lesson 8. Queueing Theory
Abstract
This Lesson presents an introduction to the stochastic analysis of queueing systems. Queueing systems arise in a variety of activities in fields such as management and technology. The applications of stochastic processes such as Markov chains, random walks and renewal processes constitute the core of the analysis.
Denis Bosq, Hung T. Nguyen
Lesson 9. Stationary Processes
Abstract
In this Lesson we point out specific properties of discrete-time weakly stationary processes. In particular, we describe the inner correlation of such a process, investigate the problem of predicting the future of a weakly stationary process, and study asymptotic theory.
Denis Bosq, Hung T. Nguyen
Lesson 10. ARMA model
Abstract
In this Lesson we introduce the popular autoregressive / Moving average (ARMA) model and study its probabilistic properties. Statistics for ARMA processes will appear in Lesson 14.
Denis Bosq, Hung T. Nguyen
Lesson 11. Discrete-Time Martingales
Abstract
A martingale is a particular sequence of dependent random variables. The concept comes from gambling systems but is also of great interest in Probability and Statistics.
Denis Bosq, Hung T. Nguyen
Lesson 12. Brownian Motion and Diffusion Processes
Abstract
This Lesson is mainly devoted to the study of continuous time processes defined by differential equations. The crucial mathematical tool is the stochastic integral.
Denis Bosq, Hung T. Nguyen
Lesson 13. Statistics for Poisson Processes
Abstract
This Lesson begins with a review of some basic concepts in Statistics. As an application we study statistical inference for Poisson processes.
Denis Bosq, Hung T. Nguyen
Lesson 14. Statistics of Discrete-Time Stationary Processes
Abstract
In this Lesson, we distinguish between nonparametric methods which appear in the general case and parametric methods which are used in ARMA models.
Denis Bosq, Hung T. Nguyen
Lesson 15. Statistics of Diffusion Processes
Abstract
This Lesson deals with statistics of continuous time processes, especially diffusion processes. Nonparametric and parametric methods are considered.
Denis Bosq, Hung T. Nguyen
Backmatter
Metadaten
Titel
A Course in Stochastic Processes
verfasst von
Denis Bosq
Hung T. Nguyen
Copyright-Jahr
1996
Verlag
Springer Netherlands
Electronic ISBN
978-94-015-8769-3
Print ISBN
978-90-481-4713-7
DOI
https://doi.org/10.1007/978-94-015-8769-3