Download or read book Stationary Processes and Prediction Theory written by Harry Furstenberg and published by Princeton University Press. This book was released on 1960-08-21 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: A classic treatment of stationary processes and prediction theory from the acclaimed Annals of Mathematics Studies series Princeton University Press is proud to have published the Annals of Mathematics Studies since 1940. One of the oldest and most respected series in science publishing, it has included many of the most important and influential mathematical works of the twentieth century. The series continues this tradition as Princeton University Press publishes the major works of the twenty-first century. To mark the continued success of the series, all books are available in paperback and as ebooks.
Download or read book Stationary Processes and Prediction Theory written by Herbert Feis and published by . This book was released on 1960 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stationary Processes and Prediction Theory AM 44 Volume 44 written by Harry Furstenberg and published by Princeton University Press. This book was released on 2016-03-02 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: A classic treatment of stationary processes and prediction theory from the acclaimed Annals of Mathematics Studies series Princeton University Press is proud to have published the Annals of Mathematics Studies since 1940. One of the oldest and most respected series in science publishing, it has included many of the most important and influential mathematical works of the twentieth century. The series continues this tradition as Princeton University Press publishes the major works of the twenty-first century. To mark the continued success of the series, all books are available in paperback and as ebooks.
Download or read book Linear Prediction on a Finite Past of a Multivariate Stationary Process written by Ray G. Langebartel and published by . This book was released on 1966 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview is given of multivariate, wide-sense, stationary, stochastic process, linear prediction theory with emphasis on the mean square error of prediction based on a finite past. Examples of several different types of processes are examined with specific formulas for the prediction errors obtained in some cases. A discussion is given concerning the effect on the prediction error of basing the prediction on a subprocess of the given process instead of on the entire original process.
Download or read book Stationary Process and Prediction Theory written by Harry Furstenberg and published by . This book was released on 1960 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Prediction Theory for Stationary Stochastic Processes written by Ralph Edward Walker and published by . This book was released on 1969 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Prediction Theory of Stationary Stochastic Processes written by Rebecca Ann Picou and published by . This book was released on 1973 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Time Series Theory and Methods written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2009-05-13 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edition contains a large number of additions and corrections scattered throughout the text, including the incorporation of a new chapter on state-space models. The companion diskette for the IBM PC has expanded into the software package ITSM: An Interactive Time Series Modelling Package for the PC, which includes a manual and can be ordered from Springer-Verlag. * We are indebted to many readers who have used the book and programs and made suggestions for improvements. Unfortunately there is not enough space to acknowledge all who have contributed in this way; however, special mention must be made of our prize-winning fault-finders, Sid Resnick and F. Pukelsheim. Special mention should also be made of Anthony Brockwell, whose advice and support on computing matters was invaluable in the preparation of the new diskettes. We have been fortunate to work on the new edition in the excellent environments provided by the University of Melbourne and Colorado State University. We thank Duane Boes particularly for his support and encouragement throughout, and the Australian Research Council and National Science Foundation for their support of research related to the new material. We are also indebted to Springer-Verlag for their constant support and assistance in preparing the second edition. Fort Collins, Colorado P. J. BROCKWELL November, 1990 R. A. DAVIS * /TSM: An Interactive Time Series Modelling Package for the PC by P. J. Brockwell and R. A. Davis. ISBN: 0-387-97482-2; 1991.
Download or read book Foundations of Time Series Analysis and Prediction Theory written by Mohsen Pourahmadi and published by John Wiley & Sons. This book was released on 2001-06-01 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of time series for researchers and students This volume provides a mathematical foundation for time seriesanalysis and prediction theory using the idea of regression and thegeometry of Hilbert spaces. It presents an overview of the tools oftime series data analysis, a detailed structural analysis ofstationary processes through various reparameterizations employingtechniques from prediction theory, digital signal processing, andlinear algebra. The author emphasizes the foundation and structureof time series and backs up this coverage with theory andapplication. End-of-chapter exercises provide reinforcement for self-study andappendices covering multivariate distributions and Bayesianforecasting add useful reference material. Further coveragefeatures: * Similarities between time series analysis and longitudinal dataanalysis * Parsimonious modeling of covariance matrices through ARMA-likemodels * Fundamental roles of the Wold decomposition andorthogonalization * Applications in digital signal processing and Kalmanfiltering * Review of functional and harmonic analysis and predictiontheory Foundations of Time Series Analysis and Prediction Theory guidesreaders from the very applied principles of time series analysisthrough the most theoretical underpinnings of prediction theory. Itprovides a firm foundation for a widely applicable subject forstudents, researchers, and professionals in diverse scientificfields.
Download or read book Non stationary Processes System Theory and Prediction written by Christian Houdré and published by . This book was released on 1987 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Prediction and Regulation by Linear Least square Methods written by Peter Whittle and published by . This book was released on 1963 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stationary and related processes; A first solution of the predction problem; Least-square approximation; Projection on the infinite sample; Projection of the semi-infinite sample; Projection on the finite sample; Deviations from stationarity: trends, deterministic components and accumulated processes; Multivariate processes; Regulation.
Download or read book Stationary Stochastic Processes for Scientists and Engineers written by Georg Lindgren and published by CRC Press. This book was released on 2013-10-11 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for a one-semester course, this text teaches students how to use stochastic processes efficiently. Carefully balancing mathematical rigor and ease of exposition, the book provides students with a sufficient understanding of the theory and a practical appreciation of how it is used in real-life situations. Special emphasis is on the interpretation of various statistical models and concepts as well as the types of questions statistical analysis can answer. To enable hands-on practice, MATLAB code is available online.
Download or read book An Introduction to the Theory of Stationary Random Functions written by A. M. Yaglom and published by Courier Corporation. This book was released on 2004-01-01 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-part treatment covers the general theory of stationary random functions and the Wiener-Kolmogorov theory of extrapolation and interpolation of random sequences and processes. Beginning with the simplest concepts, it covers the correlation function, the ergodic theorem, homogenous random fields, and general rational spectral densities, among other topics. Numerous examples appear throughout the text, with emphasis on the physical meaning of mathematical concepts. Although rigorous in its treatment, this is essentially an introduction, and the sole prerequisites are a rudimentary knowledge of probability and complex variable theory. 1962 edition.
Download or read book Stationary Stochastic Models written by Riccardo Gatto and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This volume provides a unified mathematical introduction to stationary time series models and to continuous time stationary stochastic processes. The analysis of these stationary models is carried out in time domain and in frequency domain. It begins with a practical discussion on stationarity, by which practical methods for obtaining stationary data are described. The presented topics are illustrated by numerous examples. Readers will find the following covered in a comprehensive manner: Autoregressive and moving average time series. Important properties such as causality. Autocovariance function and the spectral distribution of these models. Practical topics of time series like filtering and prediction. Basic concepts and definitions on the theory of stochastic processes, such as Wiener measure and process. General types of stochastic processes such as Gaussian, selfsimilar, compound and shot noise processes. Gaussian white noise, Langevin equation and Ornstein-Uhlenbeck process. Important related themes such as mean square properties of stationary processes and mean square integration. Spectral decomposition and spectral theorem of continuous time stationary processes. This central concept is followed by the theory of linear filters and their differential equations. At the end, some selected topics such as stationary random fields, simulation of Gaussian stationary processes and results of information theory are presented. A detailed appendix containing complementary materials will assist the reader with many technical aspects of the book"--
Download or read book Time Series Models written by Manfred Deistler and published by Springer Nature. This book was released on 2022-10-21 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.
Download or read book Foundations of the Prediction Process written by Frank B. Knight and published by . This book was released on 1992 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a unified treatment of the prediction process approach to continuous time stochastic processes. The underling idea is that there are two kinds of time: stationary physical time and the moving observer's time. By developing this theme, the author develops a theory of stochastic processes whereby two processes are considered which coexist on the same probability space. In this way, the observer' process is strongly Markovian. Consequently, any measurable stochastic process of a real parameter may be regarded as a homogeneous strong Markov process in an appropriate setting. This leads to a unifying principle for the representation of general processes in terms of martingales which facilitates the prediction of their properties. While the ideas are advanced, the methods are reasonable elementary and should be accessible to readers with basic knowledge of measure theory, functional analysis, stochastic integration, and probability on the level of the convergence theorem for positive super-martingales.
Download or read book Wide Sense Stationary Processes and Prediction written by Jon Aaronson and published by . This book was released on 1972* with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
