stochastic course notes with R

Jim Lindsey james.lindsey at
Wed Oct 17 12:49:29 CEST 2001

I have just put the postscript file for the first draft of a
manuscript of a course on The Statistical Analysis of Stochastic
Processes in Time, as well as the R code to do all of the examples, on
my web page at

The chapters are
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. Dynamic models.
 8. More complex dependencies.
Part III Continuous state space
 9. Time series.
10. Growth curves.
11. Dynamic models.
12. Repeated measurements.

Although it contains chapters on survival analysis and time series, as
far as I have been able to see, the ts and survival libraries are not
capable of performing the analyses that I required, except for some of
the simple plots.

As a reminder, the following books all have complete R code available
on my web page as well:

Introductory Statistics. A Modelling Approach. OUP, 1995 0-19-852345-9
	(also instructor's manual can be downloaded)
Models for Repeated Measurements. (2nd edn) OUP, 1999 0-19-850559-0
Nonlinear Models in Medical Statistics. OUP, 2001 0-19-850812-3

Of course, all four require my R libraries available at

Comments and criticisms are very welcome.

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