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Author : John Haywood
Publisher :
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4.:/5 (318 download)
Download or read book An Improved State Space Representation for Cyclical Time Series written by John Haywood and published by . This book was released on 1999 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Masanao Aoki
Publisher : Springer Science & Business Media
ISBN 13 : 3642758835
Total Pages : 339 pages
Book Rating : 4.6/5 (427 download)
Download or read book State Space Modeling of Time Series written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the author adopts a state space approach to time series modeling to provide a new, computer-oriented method for building models for vector-valued time series. This second edition has been completely reorganized and rewritten. Background material leading up to the two types of estimators of the state space models is collected and presented coherently in four consecutive chapters. New, fuller descriptions are given of state space models for autoregressive models commonly used in the econometric and statistical literature. Backward innovation models are newly introduced in this edition in addition to the forward innovation models, and both are used to construct instrumental variable estimators for the model matrices. Further new items in this edition include statistical properties of the two types of estimators, more details on multiplier analysis and identification of structural models using estimated models, incorporation of exogenous signals and choice of model size. A whole new chapter is devoted to modeling of integrated, nearly integrated and co-integrated time series.
Author : James Durbin
Publisher : Oxford University Press
ISBN 13 : 9780198523543
Total Pages : 280 pages
Book Rating : 4.5/5 (235 download)
Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by Oxford University Press. This book was released on 2001-06-21 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space time series analysis emerged in the 1960s in engineering, but its applications have spread to other fields. Durbin (statistics, London School of Economics and Political Science) and Koopman (econometrics, Free U., Amsterdam) extol the virtues of such models over the main analytical system currently used for time series data, Box-Jenkins' ARIMA. What distinguishes state space time models is that they separately model components such as trend, seasonal, regression elements and disturbance terms. Part I focuses on traditional and new techniques based on the linear Gaussian model. Part II presents new material extending the state space model to non-Gaussian observations. c. Book News Inc.
Author : James Durbin
Publisher : Oxford University Press
ISBN 13 : 019964117X
Total Pages : 369 pages
Book Rating : 4.1/5 (996 download)
Download or read book Time Series Analysis by State Space Methods written by James Durbin and published by Oxford University Press. This book was released on 2012-05-03 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive treatment of the state space approach to time series analysis. A distinguishing feature of state space time series models is that observations are regarded as made up of distinct components, which are each modelled separately.
Author : Jacques J. F. Commandeur
Publisher : OUP Oxford
ISBN 13 : 0191607800
Total Pages : 192 pages
Book Rating : 4.1/5 (916 download)
Download or read book An Introduction to State Space Time Series Analysis written by Jacques J. F. Commandeur and published by OUP Oxford. This book was released on 2007-07-19 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a practical introduction to state space methods as applied to unobserved components time series models, also known as structural time series models, this book introduces time series analysis using state space methodology to readers who are neither familiar with time series analysis, nor with state space methods. The only background required in order to understand the material presented in the book is a basic knowledge of classical linear regression models, of which a brief review is provided to refresh the reader's knowledge. Also, a few sections assume familiarity with matrix algebra, however, these sections may be skipped without losing the flow of the exposition. The book offers a step by step approach to the analysis of the salient features in time series such as the trend, seasonal, and irregular components. Practical problems such as forecasting and missing values are treated in some detail. This useful book will appeal to practitioners and researchers who use time series on a daily basis in areas such as the social sciences, quantitative history, biology and medicine. It also serves as an accompanying textbook for a basic time series course in econometrics and statistics, typically at an advanced undergraduate level or graduate level.
Author : Jose Casals
Publisher : CRC Press
ISBN 13 : 131536025X
Total Pages : 286 pages
Book Rating : 4.3/5 (153 download)
Download or read book State-Space Methods for Time Series Analysis written by Jose Casals and published by CRC Press. This book was released on 2018-09-03 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.
Author :
Publisher :
ISBN 13 :
Total Pages : 756 pages
Book Rating : 4.:/5 (7 download)
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 2001 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Robert H. Shumway
Publisher :
ISBN 13 : 9781475732627
Total Pages : 568 pages
Book Rating : 4.7/5 (326 download)
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Junichiro Hagiwara
Publisher : Springer Nature
ISBN 13 : 9811607117
Total Pages : 350 pages
Book Rating : 4.8/5 (116 download)
Download or read book Time Series Analysis for the State-Space Model with R/Stan written by Junichiro Hagiwara and published by Springer Nature. This book was released on 2021-08-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and concrete illustration of time series analysis focusing on the state-space model, which has recently attracted increasing attention in a broad range of fields. The major feature of the book lies in its consistent Bayesian treatment regarding whole combinations of batch and sequential solutions for linear Gaussian and general state-space models: MCMC and Kalman/particle filter. The reader is given insight on flexible modeling in modern time series analysis. The main topics of the book deal with the state-space model, covering extensively, from introductory and exploratory methods to the latest advanced topics such as real-time structural change detection. Additionally, a practical exercise using R/Stan based on real data promotes understanding and enhances the reader’s analytical capability.
Author : Robert Stephens
Publisher :
ISBN 13 :
Total Pages : 50 pages
Book Rating : 4.:/5 (318 download)
Download or read book Below the Line written by Robert Stephens and published by . This book was released on 2000 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Masanao Aoki
Publisher : Springer Science & Business Media
ISBN 13 : 1461222524
Total Pages : 335 pages
Book Rating : 4.4/5 (612 download)
Download or read book Applications of Computer Aided Time Series Modeling written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book consists of three parts: Part One is composed of two introductory chapters. The first chapter provides an instrumental varible interpretation of the state space time series algorithm originally proposed by Aoki (1983), and gives an introductory account for incorporating exogenous signals in state space models. The second chapter, by Havenner, gives practical guidance in apply ing this algorithm by one of the most experienced practitioners of the method. Havenner begins by summarizing six reasons state space methods are advanta geous, and then walks the reader through construction and evaluation of a state space model for four monthly macroeconomic series: industrial production in dex, consumer price index, six month commercial paper rate, and money stock (Ml). To single out one of the several important insights in modeling that he shares with the reader, he discusses in Section 2ii the effects of sampling er rors and model misspecification on successful modeling efforts. He argues that model misspecification is an important amplifier of the effects of sampling error that may cause symplectic matrices to have complex unit roots, a theoretical impossibility. Correct model specifications increase efficiency of estimators and often eliminate this finite sample problem. This is an important insight into the positive realness of covariance matrices; positivity has been emphasized by system engineers to the exclusion of other methods of reducing sampling error and alleviating what is simply a finite sample problem. The second and third parts collect papers that describe specific applications.
Author : Charles R. Nelson
Publisher :
ISBN 13 :
Total Pages : 19 pages
Book Rating : 4.:/5 (178 download)
Download or read book Spurious Trend and Cycle in the State Space Decomposition of a Time Series with a Unit Root written by Charles R. Nelson and published by . This book was released on 1987 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent research has proposed the state space (88) framework for decomposition of GNP and other economic time series into trend and cycle components, using the Kalman filter. This paper reviews the empirical evidence and suggests that the resulting decomposition may be spurious, just as detrending by linear regression is known to generate spurious trends and cycles in nonstationary time series. A Monte Carlo experiment confirms that when data is generated by a random walk, the 88 model tends to indicate (incorrectly) that the series consists of cyclical variations around a smooth trend. The improvement in fit over the true model will typically appear to be statistically significant. These results suggest that caution should be exercised in drawing inferences about the nature of economic processes from the 88 decomposition.
Author : Chris Brooks
Publisher : Cambridge University Press
ISBN 13 : 1108526403
Total Pages : 979 pages
Book Rating : 4.1/5 (85 download)
Download or read book Introductory Econometrics for Finance written by Chris Brooks and published by Cambridge University Press. This book was released on 2019-03-28 with total page 979 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python software guides.
Author : Kai Ming Lee
Publisher : Rozenberg Publishers
ISBN 13 : 9036101697
Total Pages : 150 pages
Book Rating : 4.0/5 (361 download)
Download or read book Filtering None-Linear State Space Models. Methods and Economic Applications written by Kai Ming Lee and published by Rozenberg Publishers. This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : John Haywood
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (318 download)
Download or read book On Log-transformations, Vector Autoregressions and Empirical Evidence written by John Haywood and published by . This book was released on 2000 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Arturo Román Messina
Publisher : CRC Press
ISBN 13 : 1000065936
Total Pages : 170 pages
Book Rating : 4.0/5 ( download)
Download or read book Data Fusion and Data Mining for Power System Monitoring written by Arturo Román Messina and published by CRC Press. This book was released on 2020-06-03 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and efficient methods to cluster and visualize data collected from multiple sensors are discussed. Both linear and nonlinear data-driven mining and fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved in realistic monitoring, visualization, and analysis of observation data from actual events are also emphasized, supported by examples of relevant applications. Features Focuses on systematic illustration of data mining and fusion in power systems Covers issues of standards used in the power industry for data mining and data analytics Applications to a wide range of power networks are provided including distribution and transmission networks Provides holistic approach to the problem of data mining and data fusion using cutting-edge methodologies and technologies Includes applications to massive spatiotemporal data from simulations and actual events
Author : John C. Brocklebank, Ph.D.
Publisher : SAS Institute
ISBN 13 : 1629605441
Total Pages : 384 pages
Book Rating : 4.6/5 (296 download)
Download or read book SAS for Forecasting Time Series, Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.
