This work looks at the numerical study of complex stochastic systems. The contributions feature several applications of these methods, such as the application to computer imaging analysis, the properties and controls of large computer networks and expert systems.
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"this book has achieved its aim of providing well-written tutorial papers for researchers by leading experts in several important areas of statisticsthe book as a whole is well deserving of a position on any researcher statistician's bookshelf" --N. Sheehan, Biometrics, June 2001 "[includes] an outstanding primer on Markov chain Monte Carlo (MCMC)it is one of the best available tutorial sources on contemporary MCMC procedures." --Journal of Mathematical Psychology "One often has reservations about edited volumes, but this one is an excellent introduction to some of the most important tools of modern statistics." -Short Book Reviews, Vol. 21, No. 2, August 2001
Current research on statistical topics spans a wide range of ideas and fields of application. Much is connected with the systematic theory of methods for the analysis of empirical data, especially for situations, common in many areas of science and technology, where the random or haphazard element in the data is too strong to be ignored. Modern computer technology has allowed the development of new methods, appealing graphical displays of analyses and also the application of ideas long known in principle but until relatively recently too complicated for other than occasional use. In an important band of applications the complex structure and large volume of data are of the essence rather than an incidental complication. In 1986 the Science and Engineering Research Council recognized the existence of these newer kinds of application by launching an Initiative under the name Complex Stochastic Systems. The papers included in this volume represent part of the work supported under that Initiative.
Topics covered include the study of large communication networks, statistical image analysis, probabilistic expert systems, statistical calibration, and innovative numerical integration techniques required in a variety of contexts associated with Complex Stochastic Systems. Taken together, the papers illustrate the blend in modern statistics of basic methodology, supported by state-of-the-art computational and graphics facilities, with influential applicability in areas of endeavour such as telecommunications, medical diagnosis, chemometrics, remote sensing, medical imaging and many other branches of science, technology and industry."About this title" may belong to another edition of this title.
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