Estimation of Stochastic Processes with Missing Observations

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Publisher :
ISBN 13 : 9781536158908
Total Pages : 0 pages
Book Rating : 4.1/5 (589 download)

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Book Synopsis Estimation of Stochastic Processes with Missing Observations by : Mikhail Moklyachuk

Download or read book Estimation of Stochastic Processes with Missing Observations written by Mikhail Moklyachuk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose results of the investigation of the problem of mean square optimal estimation of linear functionals constructed from unobserved values of stationary stochastic processes. Estimates are based on observations of the processes with additive stationary noise process. The aim of the book is to develop methods for finding the optimal estimates of the functionals in the case where some observations are missing. Formulas for computing values of the mean-square errors and the spectral characteristics of the optimal linear estimates of functionals are derived in the case of spectral certainty, where the spectral densities of the processes are exactly known. The minimax robust method of estimation is applied in the case of spectral uncertainty, where the spectral densities of the processes are not known exactly while some classes of admissible spectral densities are given. The formulas that determine the least favourable spectral densities and the minimax spectral characteristics of the optimal estimates of functionals are proposed for some special classes of admissible densities.

Statistical Analysis of Stochastic Processes in Time

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Publisher : Cambridge University Press
ISBN 13 : 9781139454513
Total Pages : 356 pages
Book Rating : 4.4/5 (545 download)

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Book Synopsis Statistical Analysis of Stochastic Processes in Time by : J. K. Lindsey

Download or read book Statistical Analysis of Stochastic Processes in Time written by J. K. Lindsey and published by Cambridge University Press. This book was released on 2004-08-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book was first published in 2004. Many observed phenomena, from the changing health of a patient to values on the stock market, are characterised by quantities that vary over time: stochastic processes are designed to study them. This book introduces practical methods of applying stochastic processes to an audience knowledgeable only in basic statistics. It covers almost all aspects of the subject and presents the theory in an easily accessible form that is highlighted by application to many examples. These examples arise from dozens of areas, from sociology through medicine to engineering. Complementing these are exercise sets making the book suited for introductory courses in stochastic processes. Software (available from www.cambridge.org) is provided for the freely available R system for the reader to apply to all the models presented.

Statistical Inference from Stochastic Processes

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Publisher : American Mathematical Soc.
ISBN 13 : 0821850873
Total Pages : 406 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Statistical Inference from Stochastic Processes by : Narahari Umanath Prabhu

Download or read book Statistical Inference from Stochastic Processes written by Narahari Umanath Prabhu and published by American Mathematical Soc.. This book was released on 1988 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. This book provides students and researchers with a familiarity with the foundations of inference from stochastic processes and intends to provide a knowledge of the developments.

Nonparametric Statistics for Stochastic Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 146840489X
Total Pages : 181 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Nonparametric Statistics for Stochastic Processes by : Denis Bosq

Download or read book Nonparametric Statistics for Stochastic Processes written by Denis Bosq and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a mathematically rigorous treatment of the theory of nonparametric estimation and prediction for stochastic processes. It discusses discrete time and continuous time, and the emphasis is on the kernel methods. Several new results are presented concerning optimal and superoptimal convergence rates. How to implement the method is discussed in detail and several numerical results are presented. This book will be of interest to specialists in mathematical statistics and to those who wish to apply these methods to practical problems involving time series analysis.

Statistical Inferences for Stochasic Processes

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Publisher : Academic Press
ISBN 13 :
Total Pages : 464 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Statistical Inferences for Stochasic Processes by : Ishwar V. Basawa

Download or read book Statistical Inferences for Stochasic Processes written by Ishwar V. Basawa and published by Academic Press. This book was released on 1980-01-28 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory examples of stochastic models; Special models; General theory; Further approaches.

Statistical Estimation

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Publisher : Springer Science & Business Media
ISBN 13 : 1489900276
Total Pages : 410 pages
Book Rating : 4.4/5 (899 download)

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Book Synopsis Statistical Estimation by : I.A. Ibragimov

Download or read book Statistical Estimation written by I.A. Ibragimov and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: when certain parameters in the problem tend to limiting values (for example, when the sample size increases indefinitely, the intensity of the noise ap proaches zero, etc.) To address the problem of asymptotically optimal estimators consider the following important case. Let X 1, X 2, ... , X n be independent observations with the joint probability density !(x,O) (with respect to the Lebesgue measure on the real line) which depends on the unknown patameter o e 9 c R1. It is required to derive the best (asymptotically) estimator 0:( X b ... , X n) of the parameter O. The first question which arises in connection with this problem is how to compare different estimators or, equivalently, how to assess their quality, in terms of the mean square deviation from the parameter or perhaps in some other way. The presently accepted approach to this problem, resulting from A. Wald's contributions, is as follows: introduce a nonnegative function w(0l> ( ), Ob Oe 9 (the loss function) and given two estimators Of and O! n 2 2 the estimator for which the expected loss (risk) Eown(Oj, 0), j = 1 or 2, is smallest is called the better with respect to Wn at point 0 (here EoO is the expectation evaluated under the assumption that the true value of the parameter is 0). Obviously, such a method of comparison is not without its defects.

Stochastic Processes, Estimation, and Control

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Publisher : SIAM
ISBN 13 : 0898716551
Total Pages : 391 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Stochastic Processes, Estimation, and Control by : Jason L. Speyer

Download or read book Stochastic Processes, Estimation, and Control written by Jason L. Speyer and published by SIAM. This book was released on 2008-11-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors provide a comprehensive treatment of stochastic systems from the foundations of probability to stochastic optimal control. The book covers discrete- and continuous-time stochastic dynamic systems leading to the derivation of the Kalman filter, its properties, and its relation to the frequency domain Wiener filter aswell as the dynamic programming derivation of the linear quadratic Gaussian (LQG) and the linear exponential Gaussian (LEG) controllers and their relation to HÝsubscript 2¨ and HÝsubscript Ýinfinity¨¨ controllers and system robustness. This book is suitable for first-year graduate students in electrical, mechanical, chemical, and aerospace engineering specializing in systems and control. Students in computer science, economics, and possibly business will also find it useful.

Statistical Estimation for Stochastic Processes

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Publisher : Kingston, Ont. : Queen's University
ISBN 13 :
Total Pages : 286 pages
Book Rating : 4.3/5 (121 download)

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Book Synopsis Statistical Estimation for Stochastic Processes by : K. Nanthi

Download or read book Statistical Estimation for Stochastic Processes written by K. Nanthi and published by Kingston, Ont. : Queen's University. This book was released on 1983 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Methods for Stochastic Differential Equations

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Publisher : CRC Press
ISBN 13 : 1439849765
Total Pages : 507 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Statistical Methods for Stochastic Differential Equations by : Mathieu Kessler

Download or read book Statistical Methods for Stochastic Differential Equations written by Mathieu Kessler and published by CRC Press. This book was released on 2012-05-17 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th

Modelling and Application of Stochastic Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 9780898381771
Total Pages : 310 pages
Book Rating : 4.3/5 (817 download)

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Book Synopsis Modelling and Application of Stochastic Processes by : Uday B. Desai

Download or read book Modelling and Application of Stochastic Processes written by Uday B. Desai and published by Springer Science & Business Media. This book was released on 1986-10-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side, chapters on use of Markov random fields for modelling and analyzing image signals, use of complementary models for the smoothing problem with missing data, and nonlinear estimation are included. Chapter 1 by Klein and Dickinson develops the nested orthogonal state space realization for ARMA processes. As suggested by the name, nested orthogonal realizations possess two key properties; (i) the state variables are orthogonal, and (ii) the system matrices for the (n + l)st order realization contain as their "upper" n-th order blocks the system matrices from the n-th order realization (nesting property).

Adventures in Stochastic Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 1461203872
Total Pages : 640 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Adventures in Stochastic Processes by : Sidney I. Resnick

Download or read book Adventures in Stochastic Processes written by Sidney I. Resnick and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic processes are necessary ingredients for building models of a wide variety of phenomena exhibiting time varying randomness. This text offers easy access to this fundamental topic for many students of applied sciences at many levels. It includes examples, exercises, applications, and computational procedures. It is uniquely useful for beginners and non-beginners in the field. No knowledge of measure theory is presumed.

Statistics of Random Processes II

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Publisher : Springer Science & Business Media
ISBN 13 : 9783540639282
Total Pages : 428 pages
Book Rating : 4.6/5 (392 download)

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Book Synopsis Statistics of Random Processes II by : Robert Shevilevich Lipt︠s︡er

Download or read book Statistics of Random Processes II written by Robert Shevilevich Lipt︠s︡er and published by Springer Science & Business Media. This book was released on 2001 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Written by two renowned experts in the field, the books under review contain a thorough and insightful treatment of the fundamental underpinnings of various aspects of stochastic processes as well as a wide range of applications. Providing clear exposition, deep mathematical results, and superb technical representation, they are masterpieces of the subject of stochastic analysis and nonlinear filtering....These books...will become classics." --SIAM REVIEW

Stochastic Methods for Estimation and Problem Solving in Engineering

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Publisher : IGI Global
ISBN 13 : 1522550461
Total Pages : 291 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Stochastic Methods for Estimation and Problem Solving in Engineering by : Kadry, Seifedine

Download or read book Stochastic Methods for Estimation and Problem Solving in Engineering written by Kadry, Seifedine and published by IGI Global. This book was released on 2018-03-02 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilizing mathematical algorithms is an important aspect of recreating real-world problems in order to make important decisions. By generating a randomized algorithm that produces statistical patterns, it becomes easier to find solutions to countless situations. Stochastic Methods for Estimation and Problem Solving in Engineering provides emerging research on the role of random probability systems in mathematical models used in various fields of research. While highlighting topics, such as random probability distribution, linear systems, and transport profiling, this book explores the use and behavior of uncertain probability methods in business and science. This book is an important resource for engineers, researchers, students, professionals, and practitioners seeking current research on the challenges and opportunities of non-deterministic probability models.

Parameter Estimation in Stochastic Differential Equations

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Publisher : Springer
ISBN 13 : 3540744487
Total Pages : 271 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Parameter Estimation in Stochastic Differential Equations by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Differential Equations written by Jaya P. N. Bishwal and published by Springer. This book was released on 2007-09-26 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parameter estimation in stochastic differential equations and stochastic partial differential equations is the science, art and technology of modeling complex phenomena. The subject has attracted researchers from several areas of mathematics. This volume presents the estimation of the unknown parameters in the corresponding continuous models based on continuous and discrete observations and examines extensively maximum likelihood, minimum contrast and Bayesian methods.

Statistical Inference for Ergodic Diffusion Processes

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Publisher : Springer Science & Business Media
ISBN 13 : 144713866X
Total Pages : 493 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Statistical Inference for Ergodic Diffusion Processes by : Yury A. Kutoyants

Download or read book Statistical Inference for Ergodic Diffusion Processes written by Yury A. Kutoyants and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.

Stochastic Processes

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Publisher : Cambridge University Press
ISBN 13 : 1107039754
Total Pages : 559 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Stochastic Processes by : Robert G. Gallager

Download or read book Stochastic Processes written by Robert G. Gallager and published by Cambridge University Press. This book was released on 2013-12-12 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive textbook on stochastic processes, written by one of the world's leading information theorists, covering both theory and applications.

Stochastic Processes, Finance And Control: A Festschrift In Honor Of Robert J Elliott

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Publisher : World Scientific
ISBN 13 : 9814483915
Total Pages : 605 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Stochastic Processes, Finance And Control: A Festschrift In Honor Of Robert J Elliott by : Samuel N Cohen

Download or read book Stochastic Processes, Finance And Control: A Festschrift In Honor Of Robert J Elliott written by Samuel N Cohen and published by World Scientific. This book was released on 2012-08-10 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of a series of new, peer-reviewed papers in stochastic processes, analysis, filtering and control, with particular emphasis on mathematical finance, actuarial science and engineering. Paper contributors include colleagues, collaborators and former students of Robert Elliott, many of whom are world-leading experts and have made fundamental and significant contributions to these areas.This book provides new important insights and results by eminent researchers in the considered areas, which will be of interest to researchers and practitioners. The topics considered will be diverse in applications, and will provide contemporary approaches to the problems considered. The areas considered are rapidly evolving. This volume will contribute to their development, and present the current state-of-the-art stochastic processes, analysis, filtering and control.Contributing authors include: H Albrecher, T Bielecki, F Dufour, M Jeanblanc, I Karatzas, H-H Kuo, A Melnikov, E Platen, G Yin, Q Zhang, C Chiarella, W Fleming, D Madan, R Mamon, J Yan, V Krishnamurthy.