Stable Non Gaussian Random Processes Pdf
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Stable Non-Gaussian Random Processes
Both an introduction and a basic reference text on non-Gaussian stable models, for graduate students and practitioners. Assuming only a first-year graduate course in probability, it includes material which has only recently appeared in journals and unpublished materials. Each chapter begins with a brief overview and concludes with a range of exercises at varying levels of difficulty. Proofs are spelled out in detail. The volume includes a discussion of self-similar processes, ARMA, and fractional ARIMA time series with stable innovations. Annotation copyright by Book News, Inc., Portland, OR
Random Processes for Engineers
Author: Bruce Hajek
language: en
Publisher: Cambridge University Press
Release Date: 2015-03-12
An engaging introduction to the critical tools needed to design and evaluate engineering systems operating in uncertain environments.
Introduction to Econophysics
Author: Rosario N. Mantegna
language: en
Publisher: Cambridge University Press
Release Date: 1999-11-13
This book concerns the use of concepts from statistical physics in the description of financial systems. The authors illustrate the scaling concepts used in probability theory, critical phenomena, and fully developed turbulent fluids. These concepts are then applied to financial time series. The authors also present a stochastic model that displays several of the statistical properties observed in empirical data. Statistical physics concepts such as stochastic dynamics, short- and long-range correlations, self-similarity and scaling permit an understanding of the global behaviour of economic systems without first having to work out a detailed microscopic description of the system. Physicists will find the application of statistical physics concepts to economic systems interesting. Economists and workers in the financial world will find useful the presentation of empirical analysis methods and well-formulated theoretical tools that might help describe systems composed of a huge number of interacting subsystems.