Statistical Analysis of Stochastic Processes in Time

This 2004 book introduces ways of modelling phenomena that occur over time. Covers stochastic processes, survival analysis, time series and more.

J. K. Lindsey (Author)

9781107405325, Cambridge University Press

Paperback / softback, published 19 July 2012

354 pages
24.4 x 17 x 1.9 cm, 0.57 kg

'… the book fills a gap between the more fundamental, topical volumes around, and more popular texts on these matters. it is very well readable, and it provides both an excellent introduction and a good overview over much of stochastic methods applicable in longitudinal data.' Environmental and Ecological Statistics

This book was first published in 2004. 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. This book introduces 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.

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.

Subject Areas: Stochastics [PBWL], Probability & statistics [PBT]