Statistical Analysis of Stochastic Processes in Time

Cambridge Series in Statistical and Probabilistic Mathematics #14

by J.K. Lindsey

Many observed phenomena, from the changing health of a patient to values on the stock market, are characterized 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 the basics of 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 is provided within the freely available R system for the reader to be able to apply all the models presented.

352 pages, Kindle Edition

First published August 2, 2004

Reviews

[Andrewcharles420 · Rating 3 out of 5]

Good introduction to many statistical tools for analyzing various random processes in time. I could have used more frequent explicit numerical calculations and/or answers to exercises. I would also liked to have better understood the meanings of the best fit parameters in the various models described in the examples, but part of that lack of understanding is my lack of familiarity and application of several of the candidate distributions.