Handbook of Statistics 21: Stochastic Processes: Modeling and Simulation

D. N. Shanbhag, C. Radhakrishna Rao0444500138, 9780444500137

Handbook of Statistics 21 This is a sequel to volume 19 of Handbook of Statistics on Stochastic Processes: Modelling and Simulation. It is concerned mainly with the theme of reviewing and in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value theory, applications of Markov chains, modelling with Monte carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. (A complete list of the topics addressed in the volume is available from the “Contents” of the volume.)”

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Table of contents :
Handbook of Statistics 21: Stochastic Processes: Modeling and Simulation……Page 1
Table of contents……Page 3
Preface……Page 11
Contributors……Page 12
1. Modeling and Numerical Methods in Manufacturing System Using Control Theory……Page 15
2. Models of Random Graphs and their Applications……Page 64
3. Locally Self-Similar Processes and their Wavelet Analysis……Page 105
4. Stochastic Models for DNA Replication……Page 148
5. An Empirical Process with Applications to Testing the Exponential and Geometric Models……Page 178
6. Patterns in Sequences of Random Events……Page 237
7. Stochastic Models in Telecommunications for Optimal Design, Control and Performance Evaluation……Page 253
8. Stochastic Processes in Epidemic Modelling and Simulation……Page 295
9. Empirical Estimators Based on MCMC Data……Page 346
10. Fractals and the Modelling of Self-Similarity……Page 380
11. Numerical Methods in Queueing Theory……Page 416
12. Applications of Markov Chains to the Distribution Theory of Runs and Patterns……Page 439
13. Modeling Image Analysis Problems Using Markov Random Fields……Page 481
14. An Introduction to Semi-Markov Processes with Application to Reliability……Page 522
15. Departures and Related Characteristics in Queueing Models……Page 564
16. Discrete Variate Time Series……Page 580
17. Extreme Value Theory, Models and Simulation……Page 614
18. Biological Applications of Branching Processes……Page 699
19. Markov Chain Approaches to Damage Models……Page 780
20. Point Processes in Astronomy: Exciting Events in the Universe……Page 800
21. On the Theory of Discrete and Continuous Bilinear Time Series Models……Page 831
22. Nonlinear and Non-Gaussian State-Space Modeling with Monte Carlo Techniques: A Survey and Comparative Study……Page 875
23. Markov Modelling of Burst Behaviour in Ion Channels……Page 934
Subject Index……Page 972
Handbook of Statistics: Contents of Previous Volumes……Page 982