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
Stochastic Processes: Modeling and Simulation
โ Scribed by D. N. Shanbhag, C. Radhakrishna Rao
- Publisher
- Elsevier Publishing Company
- Year
- 2003
- Tongue
- English
- Leaves
- 993
- Series
- Handbook of Statistics 21
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.)
An attempt is made to cover in this volume, as in the case of its predec
๐ SIMILAR VOLUMES
<div>A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors
Stochastic Processes and Models provides a concise and lucid introduction to simple stochastic processes and models. Including numerous exercises, problems and solutions, it covers the key concepts and tools, in particular: randon walks, renewals, Markov chains, martingales, the Wiener process mode
Stochastic Processes and Models provides a concise and lucid introduction to simple stochastic processes and models. Including numerous exercises, problems and solutions, it covers the key concepts and tools, in particular: randon walks, renewals, Markov chains, martingales, the Wiener process mode