Statistical Analysis of Stochastic Processes in Time

J.K. Lindsey - Collection Cambridge series in statistical and probabilistic mathematics

338 pages, parution le 01/10/2004

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Résumé

Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. Much theoretical work has been done but virtually no modern books are available to show how the results can be applied. This book fills that gap by introducing practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.

L'auteur - J.K. Lindsey

Limburgs Universitair Centrum, Diepenbeek, Belgium

Sommaire

Preface
Basic Principles
- What is a stochastic process?
- Normal theory models and extensions
Categorical State Space
- Survival processes
- Recurrent events
- Discrete-time Markov chains
- Event histories
- Dynamics models
- More complex dependencies
Continuous State Space
- Time series
- Growth curves
- Dynamic models
- Repeated measurements

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Cambridge University Press
Auteur(s)	J.K. Lindsey
Collection	Cambridge series in statistical and probabilistic mathematics
Parution	01/10/2004
Nb. de pages	338
Format	18 x 26
Couverture	Relié
Poids	789g
Intérieur	Noir et Blanc
EAN13	9780521837415
ISBN13	978-0-521-83741-5