Non-Stationary Stochastic Processes Estimation
Non-Stationary Stochastic Processes Estimation

Author: Maksym Luz

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2024-05-20

Total Pages: 310

ISBN-13: 3111325628

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The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word. Methods of stochastic processes estimation depend on two main factors. The first factor is construction of a model of the process being investigated. The second factor is the available information about the structure of the process under consideration. In this book, we propose results of the investigation of the problem of mean square optimal estimation (extrapolation, interpolation, and filtering) of linear functionals depending on unobserved values of stochastic sequences and processes with periodically stationary and long memory multiplicative seasonal increments. Formulas for calculating the mean square errors and the spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral structure of the considered sequences and processes are exactly known. In the case where spectral densities of the sequences and processes are not known exactly while some sets of admissible spectral densities are given, we apply the minimax-robust method of estimation.

Estimation of Stochastic Processes with Missing Observations
Estimation of Stochastic Processes with Missing Observations

Author: Mikhail Moklyachuk

Publisher:

Published: 2019

Total Pages: 0

ISBN-13: 9781536158908

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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.

Stationary Stochastic Processes for Scientists and Engineers
Stationary Stochastic Processes for Scientists and Engineers

Author: Georg Lindgren

Publisher: CRC Press

Published: 2013-10-11

Total Pages: 316

ISBN-13: 1466586192

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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.

Nonstationary Stochastic Processes And Their Applications - Proceedings Of The Workshop
Nonstationary Stochastic Processes And Their Applications - Proceedings Of The Workshop

Author: Abolghassem G Miamee

Publisher: World Scientific

Published: 1992-08-08

Total Pages: 298

ISBN-13: 9814554502

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The purpose of the workshop was to bring together researchers working in a broad spectrum of nonstationary stochastic processes to present their findings and techniques for analyzing the growing field of nonstationary stochastic processes. Researchers from both engineering and mathematics communities shared their sometimes different, but complementing, point of views on the recent developments in the theory and applications of nonstationary stochastic processes. As such, this volume will be of interest to mathematicians, probabilists, and engineers, and it is hoped that this will stimulate a significant amount of research in this field.

Modelling and Application of Stochastic Processes
Modelling and Application of Stochastic Processes

Author: Uday B. Desai

Publisher: Springer Science & Business Media

Published: 1986-10-31

Total Pages: 310

ISBN-13: 9780898381771

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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).

Non-Stationary Stochastic Processes Estimation
Non-Stationary Stochastic Processes Estimation

Author: Maksym Luz

Publisher:

Published: 2024-06-17

Total Pages: 0

ISBN-13: 9783111325330

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The problem of forecasting future values of economic and physical processes, the problem of restoring lost information, cleaning signals or other data observations from noise, is magnified in an information-laden word. Methods of stochastic processes estimation depend on two main factors. The first factor is construction of a model of the process being investigated. The second factor is the available information about the structure of the process under consideration. In this book, we propose results of the investigation of the problem of mean square optimal estimation (extrapolation, interpolation, and filtering) of linear functionals depending on unobserved values of stochastic sequences and processes with periodically stationary and long memory multiplicative seasonal increments. Formulas for calculating the mean square errors and the spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral structure of the considered sequences and processes are exactly known. In the case where spectral densities of the sequences and processes are not known exactly while some sets of admissible spectral densities are given, we apply the minimax-robust method of estimation.

Computational Finance and Financial Econometrics
Computational Finance and Financial Econometrics

Author: Eric Zivot

Publisher: CRC Press

Published: 2017-01-15

Total Pages: 500

ISBN-13: 9781498775779

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This book presents mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. The tools are used to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. The author explains how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.

An Author and Permuted Title Index to Selected Statistical Journals
An Author and Permuted Title Index to Selected Statistical Journals

Author: Brian L. Joiner

Publisher:

Published: 1970

Total Pages: 512

ISBN-13:

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All articles, notes, queries, corrigenda, and obituaries appearing in the following journals during the indicated years are indexed: Annals of mathematical statistics, 1961-1969; Biometrics, 1965-1969#3; Biometrics, 1951-1969; Journal of the American Statistical Association, 1956-1969; Journal of the Royal Statistical Society, Series B, 1954-1969,#2; South African statistical journal, 1967-1969,#2; Technometrics, 1959-1969.--p.iv.

Nonlinear Stochastic Mechanics
Nonlinear Stochastic Mechanics

Author: Nicola Bellomo

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 546

ISBN-13: 3642847897

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The Symposium, held in Torino (lSI, Villa Gualino) July 1-5, 1991 is the sixth of a series of IUTAM-Symposia on the application of stochastic analysis to continuum and discrete mechanics. The previous one, held in Innsbruck (1987), was mainly concentrated on qual itative and quantitative analysis of stochastic dynamical systems as well as on bifurcation and transition to chaos of deterministic systems. This Symposium concentrated on fundamental aspects (stochastic analysis and mathe matical methods), on specific applications in various branches of mechanics, engineering and applied sciences as well as on related fields as analysis of large systems, system identifica tion, earthquake prediction. Numerical methods suitable to provide quantitative results, say stochastic finite elements, approximation of probability distribution and direct integration of differential equations have also been the object of interesting presentations. Specific topics of the sessions have been: Engineering Applications, Equivalent Lineariza tion of Discrete Stochastic Systems, Fatigue and Life Estimation, Fluid Dynamics, Numerical Methods, Random Vibration, Reliability Analysis, Stochastic Differential Equations, System Identification, Stochastic Control. We are indebted to the IUTAM Bureau for having promoted and sponsored this Sympo sium and the Scientific Committee for having collaborated to the selection of participants and lecturers as well as to a prompt reviewing of the papers submitted for publication into these proceedings. A special thank is due to Frank Kozin: the organization of this meeting was for him ';ery important; he missed the meeting but his organizer ability was present.