Buch, Englisch, Band 14, 352 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 861 g
Reihe: Cambridge Series in Statistical and Probabilistic Mathematics
Buch, Englisch, Band 14, 352 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 861 g
Reihe: Cambridge Series in Statistical and Probabilistic Mathematics
ISBN: 978-0-521-83741-5
Verlag: Cambridge University Press
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.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface
Part I. Basic Principles: 1. What is a stochastic process?
2. Normal theory models and extensions
Part II. Categorical State Space: 3. Survival processes
4. Recurrent events
5. Discrete-time Markov chains
6. Event histories
7. Dynamics models
8. More complex dependencies
Part III. Continuous State Space: 9. Time series
10. Growth curves
11. Dynamic models
12. Repeated measurements
Bibliography
Author index
Subject index.
