Stochastic processes : modelling and simulation
著者
書誌事項
Stochastic processes : modelling and simulation
（Handbook of statistics, v. 21）
Elsevier, 2003
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation 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 therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.
目次
- Modelling and numerical methods in manufacturing systems using control theory, E.K. Boukas, Z.K. Liu
- models of random graphs and their applications, C. Cannings, D.B. Penman
- locally self-similar processes and their wavelet analysis, J.E. Cavanaugh, Y. Wang, J.W. Davis
- stochastic models for DNA replications, R. Cowan
- an empirical process with applications to test exponential and geometric models, J.E. Ferreira
- patterns of sequences of random events, J. Gani
- stochastic models in telecommunications for optimal design, control and performance evaluation, N. Gautam
- stochastic processes in epidemic modelling and simulation, D. Greenhalgh
- inference and simulation for random fields, P. Greenwood, W. Wefelmeyer
- modelling self-similarity - fractals and stochastic processes, B.M. Hambly
- numerical methods in queueing theory, D. Heyman
- applications of Markov chains to the distribution theory of runs and patterns, M.V. Koutras
- modelling image analysis problems using Markov random fields, S.Z. Li
- semi-Markov processes in reliability, N. Limnios, G. Oprisan
- departures and related characteristics in queueing models, M. Manoharan, M.H. Alamatsaz, D.N. Shanbhag
- discrete variate time series, E.D. McKenzie
- extreme value theory, models and simulation, S.Nadarajah
- biological applications of branching processes, A.G. Pakes
- Markov chain approaches to damage models, C.R. Rao, M. Albassam, M.B. Rao, D.N. Shanbhag
- point processes in astronomy - exciting events in the universe, J.D. Scargle, G.J. Babu
- on the theory of discrete and continuous parameter biliniear random processes, T. Subba Rao, G. Terdic
- non-linear and non-Gaussian state-space modelling with Monte Carlo techniques - a survey and comparative study, H. Tanizaki
- Markov modelling of burst behaviour in ion channels, G.F. Yeo, R.K. Milne, B.W. Madsen, Y. Li, R.O. Edeson.
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