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Forecast Of Non Stationary Time Series By Applying Locally Stationary Autoregressive Models
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Book Synopsis Forecast of Non-stationary Time Series by Applying Locally Stationary Autoregressive Models by : Junichi Kuwabara
Download or read book Forecast of Non-stationary Time Series by Applying Locally Stationary Autoregressive Models written by Junichi Kuwabara and published by . This book was released on 1995 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting Economic Time Series Using Locally Stationary Processes by : Tina Loll
Download or read book Forecasting Economic Time Series Using Locally Stationary Processes written by Tina Loll and published by Volkswirtschaftliche Analysen. This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stationarity has always played an important part in forecasting theory. However, some economic time series show time-varying autocovariances. The question arises whether forecasts can be improved using models that capture such a time-varying second-order structure. One possibility is given by autoregressive models with time-varying parameters. The author focuses on the development of a forecasting procedure for these processes and compares this approach to classical forecasting methods by means of Monte Carlo simulations. An evaluation of the proposed procedure is given by its application to futures prices and the Dow Jones index. The approach turns out to be superior to the classical methods if the sample sizes are large and the forecasting horizons do not range too far into the future.
Book Synopsis Non-linear and Non-stationary Time Series Analysis by : Maurice Bertram Priestley
Download or read book Non-linear and Non-stationary Time Series Analysis written by Maurice Bertram Priestley and published by . This book was released on 1988 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistics in Volcanology by : Heidy M. Mader
Download or read book Statistics in Volcanology written by Heidy M. Mader and published by Geological Society of London. This book was released on 2006 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics in Volcanology is a comprehensive guide to modern statistical methods applied in volcanology written by today's leading authorities. The volume aims to show how the statistical analysis of complex volcanological data sets, including time series, and numerical models of volcanic processes can improve our ability to forecast volcanic eruptions. Specific topics include the use of expert elicitation and Bayesian methods in eruption forecasting, statistical models of temporal and spatial patterns of volcanic activity, analysis of time series in volcano seismology, probabilistic hazard assessment, and assessment of numerical models using robust statistical methods. Also provided are comprehensive overviews of volcanic phenomena, and a full glossary of both volcanological and statistical terms. Statistics in Volcanology is essential reading for advanced undergraduates, graduate students, and research scientists interested in this multidisciplinary field.
Book Synopsis Analysis of Nonstationary Time Series with Time Varying Frequencies by : Henry Gray
Download or read book Analysis of Nonstationary Time Series with Time Varying Frequencies written by Henry Gray and published by Createspace Independent Publishing Platform. This book was released on 2018-06-20 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on the analysis of nonstationary processes with linearly time vary-ing periodic behavior. First we develop LM-stationary processes for analyzing time series data with linearly compacting periodic behavior. Spectral analysis using this method shows better performance than that using the Wigner-Ville time frequency distribution. The LM-stationary forecasts produce better results than autoregressive forecasts applied directly to time series data with linearly compacting periods. The second part of this thesis develops piecewise G-stationary processes and develops the piecewise M-stationary process which is capable of analyzing data with linear periodic change that is piecewise monotonic. The in-stantaneous spectrum obtained using this model is able to capture the change of frequency behavior more clearly than the standard Wigner-Ville time frequency distribution. The time varying frequency obtained using the Wigner-Ville time frequency distribution is used in the detection of the change point. LM-stationary and RM-stationary models are used in appropriate time intervals where frequencies are changing monotonically. In addition to two main developments, this thesis discusses properties of G-stationary, piecewise G-stationary and extended G-stationary processes.
Book Synopsis Forecasting in the Presence of Structural Breaks and Model Uncertainty by : David E. Rapach
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Book Synopsis Time Series Analysis: Methods and Applications by : Tata Subba Rao
Download or read book Time Series Analysis: Methods and Applications written by Tata Subba Rao and published by Elsevier. This book was released on 2012-06-26 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Handbook of Statistics' is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with volume 30 dealing with time series.
Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell
Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.
Book Synopsis Studies in the Identification and Forecasting of Non-stationary Time Series by : Dean W. Wichern
Download or read book Studies in the Identification and Forecasting of Non-stationary Time Series written by Dean W. Wichern and published by . This book was released on 1969 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Non-Linear Time Series by : Kamil Feridun Turkman
Download or read book Non-Linear Time Series written by Kamil Feridun Turkman and published by Springer. This book was released on 2014-09-29 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.
Book Synopsis Introduction to Time Series Analysis and Forecasting by : Douglas C. Montgomery
Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.
Book Synopsis Forecasting Models from Non-stationary Time Series by : Frank Charles Fuller
Download or read book Forecasting Models from Non-stationary Time Series written by Frank Charles Fuller and published by . This book was released on 1970 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Non-Stationary Stochastic Processes Estimation by : Maksym Luz
Download or read book Non-Stationary Stochastic Processes Estimation written by Maksym Luz and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-05-20 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Spectral Analysis of Time Series by : L. H. Koopmans
Download or read book The Spectral Analysis of Time Series written by L. H. Koopmans and published by Academic Press. This book was released on 2014-05-12 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Spectral Analysis of Time Series describes the techniques and theory of the frequency domain analysis of time series. The book discusses the physical processes and the basic features of models of time series. The central feature of all models is the existence of a spectrum by which the time series is decomposed into a linear combination of sines and cosines. The investigator can used Fourier decompositions or other kinds of spectrals in time series analysis. The text explains the Wiener theory of spectral analysis, the spectral representation for weakly stationary stochastic processes, and the real spectral representation. The book also discusses sampling, aliasing, discrete-time models, linear filters that have general properties with applications to continuous-time processes, and the applications of multivariate spectral models. The text describes finite parameter models, the distribution theory of spectral estimates with applications to statistical inference, as well as sampling properties of spectral estimates, experimental design, and spectral computations. The book is intended either as a textbook or for individual reading for one-semester or two-quarter course for students of time series analysis users. It is also suitable for mathematicians or professors of calculus, statistics, and advanced mathematics.
Book Synopsis Forecasting Non-stationary Economic Time Series by : Michael P. Clements
Download or read book Forecasting Non-stationary Economic Time Series written by Michael P. Clements and published by . This book was released on 1999 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Time Series Analysis: Methods and Applications by :
Download or read book Time Series Analysis: Methods and Applications written by and published by Elsevier. This book was released on 2012-05-18 with total page 777 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respective areas
Book Synopsis The Analysis of Nonstationary Time Series and Curve Estimation with Locally Stationary Models by : Rainer Dahlhaus
Download or read book The Analysis of Nonstationary Time Series and Curve Estimation with Locally Stationary Models written by Rainer Dahlhaus and published by . This book was released on 1997 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
