Non-Stationary Stochastic Processes Estimation

Non-Stationary Stochastic Processes Estimation
Author: Maksym Luz
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 310
Release: 2024-05-20
Genre: Business & Economics
ISBN: 3111325628

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.

Stationary Stochastic Processes for Scientists and Engineers

Stationary Stochastic Processes for Scientists and Engineers
Author: Georg Lindgren
Publisher: CRC Press
Total Pages: 316
Release: 2013-10-11
Genre: Mathematics
ISBN: 1466586192

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.

Estimation of Stochastic Processes with Missing Observations

Estimation of Stochastic Processes with Missing Observations
Author: Mikhail Moklyachuk
Publisher:
Total Pages: 0
Release: 2019
Genre: Missing observations (Statistics)
ISBN: 9781536158908

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.

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
Total Pages: 298
Release: 1992-08-08
Genre:
ISBN: 9814554502

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.

Change-Point Analysis in Nonstationary Stochastic Models

Change-Point Analysis in Nonstationary Stochastic Models
Author: Boris Brodsky
Publisher: CRC Press
Total Pages: 366
Release: 2016-12-12
Genre: Mathematics
ISBN: 1498755976

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures of such systems. It covers both retrospective and sequential problems, particularly theoretical methods of optimal detection. Such methods are constructed and their characteristics are analyzed both theoretically and experimentally. Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.

Nonparametric Statistics for Stochastic Processes

Nonparametric Statistics for Stochastic Processes
Author: D. Bosq
Publisher: Springer Science & Business Media
Total Pages: 219
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461217180

This book is devoted to the theory and applications of nonparametic functional estimation and prediction. Chapter 1 provides an overview of inequalities and limit theorems for strong mixing processes. Density and regression estimation in discrete time are studied in Chapter 2 and 3. The special rates of convergence which appear in continuous time are presented in Chapters 4 and 5. This second edition is extensively revised and it contains two new chapters. Chapter 6 discusses the surprising local time density estimator. Chapter 7 gives a detailed account of implementation of nonparametric method and practical examples in economics, finance and physics. Comarison with ARMA and ARCH methods shows the efficiency of nonparametric forecasting. The prerequisite is a knowledge of classical probability theory and statistics. Denis Bosq is Professor of Statistics at the Unviersity of Paris 6 (Pierre et Marie Curie). He is Editor-in-Chief of "Statistical Inference for Stochastic Processes" and an editor of "Journal of Nonparametric Statistics". He is an elected member of the International Statistical Institute. He has published about 90 papers or works in nonparametric statistics and four books.

Stationary Stochastic Processes

Stationary Stochastic Processes
Author: Georg Lindgren
Publisher: CRC Press
Total Pages: 378
Release: 2012-10-01
Genre: Mathematics
ISBN: 1466557796

Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for stationary processes and fields, including a portion on stationary point processes. Features Presents and illustrates the fundamental correlation and spectral methods for stochastic processes and random fields Explains how the basic theory is used in special applications like detection theory and signal processing, spatial statistics, and reliability Motivates mathematical theory from a statistical model-building viewpoint Introduces a selection of special topics, including extreme value theory, filter theory, long-range dependence, and point processes Provides more than 100 exercises with hints to solutions and selected full solutions This book covers key topics such as ergodicity, crossing problems, and extremes, and opens the doors to a selection of special topics, like extreme value theory, filter theory, long-range dependence, and point processes, and includes many exercises and examples to illustrate the theory. Precise in mathematical details without being pedantic, Stationary Stochastic Processes: Theory and Applications is for the student with some experience with stochastic processes and a desire for deeper understanding without getting bogged down in abstract mathematics.

Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences

Estimation of Stochastic Processes with Stationary Increments and Cointegrated Sequences
Author: Maksym Luz
Publisher: John Wiley & Sons
Total Pages: 314
Release: 2019-09-20
Genre: Mathematics
ISBN: 1119663520

Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.