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Author : Sook Fwe Yap
Publisher :
ISBN 13 :
Total Pages : 352 pages
Book Rating : 4.:/5 (89 download)
Download or read book Partially Nonstationary Multivariate Autoregressive Moving Average Models written by Sook Fwe Yap and published by . This book was released on 1992 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gregory C. Reinsel
Publisher : Springer Science & Business Media
ISBN 13 : 146840198X
Total Pages : 278 pages
Book Rating : 4.4/5 (684 download)
Download or read book Elements of Multivariate Time Series Analysis written by Gregory C. Reinsel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of methods of time series analysis in the study of multivariate time series has become of increased interest in recent years. Although the methods are rather well developed and understood for univarjate time series analysis, the situation is not so complete for the multivariate case. This book is designed to introduce the basic concepts and methods that are useful in the analysis and modeling of multivariate time series, with illustrations of these basic ideas. The development includes both traditional topics such as autocovariance and auto correlation matrices of stationary processes, properties of vector ARMA models, forecasting ARMA processes, least squares and maximum likelihood estimation techniques for vector AR and ARMA models, and model checking diagnostics for residuals, as well as topics of more recent interest for vector ARMA models such as reduced rank structure, structural indices, scalar component models, canonical correlation analyses for vector time series, multivariate unit-root models and cointegration structure, and state-space models and Kalman filtering techniques and applications. This book concentrates on the time-domain analysis of multivariate time series, and the important subject of spectral analysis is not considered here. For that topic, the reader is referred to the excellent books by Jenkins and Watts (1968), Hannan (1970), Priestley (1981), and others.
Author : Wai Keung Li
Publisher : Springer
ISBN 13 : 1493965689
Total Pages : 298 pages
Book Rating : 4.4/5 (939 download)
Download or read book Advances in Time Series Methods and Applications written by Wai Keung Li and published by Springer. This book was released on 2016-12-02 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume reviews and summarizes some of A. I. McLeod's significant contributions to time series analysis. It also contains original contributions to the field and to related areas by participants of the festschrift held in June 2014 and friends of Dr. McLeod. Covering a diverse range of state-of-the-art topics, this volume well balances applied and theoretical research across fourteen contributions by experts in the field. It will be of interest to researchers and practitioners in time series, econometricians, and graduate students in time series or econometrics, as well as environmental statisticians, data scientists, statisticians interested in graphical models, and researchers in quantitative risk management.
Author : D. M. Titterington
Publisher :
ISBN 13 : 9780198509936
Total Pages : 404 pages
Book Rating : 4.5/5 (99 download)
Download or read book Biometrika written by D. M. Titterington and published by . This book was released on 2001 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The year 2001 marks the centenary of Biometrika, one of the world's leading academic journals in statistical theory and methodology. In celebration of this, the book brings together two sets of papers from the journal. The first comprises seven specially commissioned articles (authors: D.R. Cox, A.C. Davison, Anthony C. Atkinson and R.A. Bailey, David Oakes, Peter Hall, T.M.F. Smith, and Howell Tong). These articles review the history of the journal and the most important contributions made by appearing in the journal in a number of important areas of statitisical activity, including general theory and methodology, surveys and time sets. In the process the papers describe the general development of statistical science during the twentieth century. The second group of ten papers are a selection of particularly seminal articles form the journal's first hundred years. The book opens with an introduction by the editors Professor D.M. Titterington and Sir David Cox.
Author :
Publisher :
ISBN 13 :
Total Pages : 1726 pages
Book Rating : 4.4/5 (91 download)
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 1998 with total page 1726 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Johannes Ledolter
Publisher :
ISBN 13 :
Total Pages : 48 pages
Book Rating : 4.E/5 ( download)
Download or read book The Analysis of Multivariate Time Series with a View to Applications in Hydrology written by Johannes Ledolter and published by . This book was released on 1977 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michio Hatanaka
Publisher : OUP Oxford
ISBN 13 : 0191525022
Total Pages : 310 pages
Book Rating : 4.1/5 (915 download)
Download or read book Time-Series-Based Econometrics written by Michio Hatanaka and published by OUP Oxford. This book was released on 1996-01-25 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, time-series econometrics has made extraordinary developments on unit roots and cointegration. However, this progress has taken divergent directions, and has been subjected to criticism from outside the field. In this book, Professor Hatanaka surveys the field, examines those portions that are useful for macroeconomics, and responds to the criticism. His survey of the literature covers not only econometric methods, but also the application of these methods to macroeconomic studies. The most vigorous criticism has been that unit roots to do not exist in macroeconomic variables, and thus that cointegration analysis is irrelevant to macroeconomics. The judgement of this book is that unit roots are present in macroeconomic variables when we consider periods of 20 to 40 years, but that the critics may be right when periods of 100 years are considered. Fortunately, most of the time series data used for macroeconomic studies cover fall within the shorter time span. Among the numerous methods for unit roots and cointegration, those useful from macroeconomic studies are examined and explained in detail, without overburdening the reader with unnecessary mathematics. Other, less applicable methods are dicussed briefly, and their weaknesses are exposed. Hatanaka has rigourously based his judgements about usefulness on whether the inference is appropriate for the length of the data sets available, and also on whether a proper inference can be made on the sort of propositions that macroeconomists wish to test. This book highlights the relations between cointegration and economic theories, and presents cointegrated regression as a revolution in econometric methods. Its analysis is of relevance to academic and professional or applied econometricians. Step-by-step explanations of concepts and techniques make the book a self-contained text for graduate students.
Author : Wayne A. Fuller
Publisher : John Wiley & Sons
ISBN 13 : 0470317752
Total Pages : 734 pages
Book Rating : 4.4/5 (73 download)
Download or read book Introduction to Statistical Time Series written by Wayne A. Fuller and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.
Author : Des Francis Nicholls
Publisher :
ISBN 13 : 9780909541705
Total Pages : 26 pages
Book Rating : 4.5/5 (417 download)
Download or read book The Exact Maximum Likelihood Function of Multivariate Autoregressive Moving Average Models written by Des Francis Nicholls and published by . This book was released on 1978 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Helmut Lütkepohl
Publisher : Springer Science & Business Media
ISBN 13 : 9783540569404
Total Pages : 576 pages
Book Rating : 4.5/5 (694 download)
Download or read book Introduction to Multiple Time Series Analysis written by Helmut Lütkepohl and published by Springer Science & Business Media. This book was released on 1993-08-13 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate level textbook deals with analyzing and forecasting multiple time series. It considers a wide range of multiple time series models and methods. The models include vector autoregressive, vector autoregressive moving average, cointegrated, and periodic processes as well as state space and dynamic simultaneous equations models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection or specification are treated and a range of tests and criteria for evaluating the adequacy of a chosen model are introduced. The choice of point and interval forecasts is considered and impulse response analysis, dynamic multipliers as well as innovation accounting are presented as tools for structural analysis within the multiple time series context. This book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on this book. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their task. It enables the reader to perform his or her analyses in a gap to the difficult technical literature on the topic.
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 : Marcia W. Bulach
Publisher : Universal-Publishers
ISBN 13 : 1581120559
Total Pages : 418 pages
Book Rating : 4.5/5 (811 download)
Download or read book Canonical Auto and Cross Correlations of Multivariate Time Series written by Marcia W. Bulach and published by Universal-Publishers. This book was released on 1999 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of Multivariate Time Series has always been more difficult at the modeling stage than the univariate case. Identification of a suitable model, questions of stability, and the difficulties of prediction are well recognised. A variety of methods appear to be worth examining. This thesis is concerned with the proposal of an useful tool which is to apply canonical analysis to a realisation of a Multivariate Time Series and concentrates it's attention on k-variate ARMA(p, q) models. The multivariate series is partitioned into two overlapping or non-overlapping sets of different sizes. The left set is kept at lag 0 (without loss of generality) and the right set at a sequence of lags s=0,1, ... . The model includes the possibility that the same subset of variables belong to the left set at lag 0 and to the right set at lag s. A technique for dimension reduction is suggested. We tried to elucidate identification and the internal structure of time-dependence at several pairs of lags as a tool for identification. As the technique suggested provide a method of investigation of patterns of interrelations between two multivariate sets or subsets of variables with a joint distribution, it is an efficient tool for use in multivariate series of economic data. A review of the basic models of Multivariate Time Series is given and their canonical auto and cross correlation analysis is presented. In order to study the asymptotic distribution, several Monte Carlo experiments were necessary. We attempted to provide information through simulation about the distributional and other statistical properties for the canonical statistics obtained by our procedures. New software is provided and data experience is given. The first computer program provides us with information, graphs for the canonical auto and cross correlations, test statistics for the 'useful' canonical auto and cross correlations as well as the left and right eigenvectors, left and right intraset and interset matrices of correlations, proportions of variances extracted by the canonical variates of the left and of the right sets and left and right redundancies for lags s=0,1, ... .The second program gives similar calculations for the k-variate ARMA(p, q) models when the matrices of parameters and variance-covariance matrix of the error are known. The third program provides us with the mean value, minimum and maximum values, excess kurtosis, histogram and cumulative distribution for each one of the canonical auto and cross correlations at every lag s calculated from several simulations of Monte Carlo generated k-variate ARMA(p, q) models when the matrices of parameters and variance-covariance matrix of the error are given or when they are generated. The second part of the thesis is devoted to the generalisation of the robust and practically useful univariate Holt-Winters model. We developed formula for the Multivariate Additive Holt-Winters (Seasonal and Non-Seasonal) to the point of application and its reduction to Moving Average form. New software is produced. The link between the two main themes consists on the canonical analysis of a Multivariate Holt-Winters from its reduced MA form and reducing its dimension as well as detecting the basic linear relationships between variables, between and within several lags. We also attempted to investigate the effect of outliers, the removal of non-stationary trends via cubic spline fitting, differencing as well as transformations such as loge (data).
Author : Klaus Neusser
Publisher : Springer
ISBN 13 : 331932862X
Total Pages : 421 pages
Book Rating : 4.3/5 (193 download)
Download or read book Time Series Econometrics written by Klaus Neusser and published by Springer. This book was released on 2016-06-14 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents modern developments in time series analysis and focuses on their application to economic problems. The book first introduces the fundamental concept of a stationary time series and the basic properties of covariance, investigating the structure and estimation of autoregressive-moving average (ARMA) models and their relations to the covariance structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and presenting standard statistical tests and regressions. Next, the text discusses volatility models and their applications in the analysis of financial market data, focusing on generalized autoregressive conditional heteroskedastic (GARCH) models. The second part of the text devoted to multivariate processes, such as vector autoregressive (VAR) models and structural vector autoregressive (SVAR) models, which have become the main tools in empirical macroeconomics. The text concludes with a discussion of co-integrated models and the Kalman Filter, which is being used with increasing frequency. Mathematically rigorous, yet application-oriented, this self-contained text will help students develop a deeper understanding of theory and better command of the models that are vital to the field. Assuming a basic knowledge of statistics and/or econometrics, this text is best suited for advanced undergraduate and beginning graduate students.
Author : Helmut Lütkepohl
Publisher : Cambridge University Press
ISBN 13 : 1139454730
Total Pages : 351 pages
Book Rating : 4.1/5 (394 download)
Download or read book Applied Time Series Econometrics written by Helmut Lütkepohl and published by Cambridge University Press. This book was released on 2004-08-02 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series econometrics is a rapidly evolving field. Particularly, the cointegration revolution has had a substantial impact on applied analysis. Hence, no textbook has managed to cover the full range of methods in current use and explain how to proceed in applied domains. This gap in the literature motivates the present volume. The methods are sketched out, reminding the reader of the ideas underlying them and giving sufficient background for empirical work. The treatment can also be used as a textbook for a course on applied time series econometrics. Topics include: unit root and cointegration analysis, structural vector autoregressions, conditional heteroskedasticity and nonlinear and nonparametric time series models. Crucial to empirical work is the software that is available for analysis. New methodology is typically only gradually incorporated into existing software packages. Therefore a flexible Java interface has been created, allowing readers to replicate the applications and conduct their own analyses.
Author : Tzer-Yuaan Lin
Publisher :
ISBN 13 :
Total Pages : 270 pages
Book Rating : 4.:/5 (89 download)
Download or read book An Optimization Technique for Estimation of Multivariate Autoregressive Moving Average (MARMAV) Model Paramaters written by Tzer-Yuaan Lin and published by . This book was released on 1984 with total page 270 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 : William W. S. Wei
Publisher : John Wiley & Sons
ISBN 13 : 1119502853
Total Pages : 536 pages
Book Rating : 4.1/5 (195 download)
Download or read book Multivariate Time Series Analysis and Applications written by William W. S. Wei and published by John Wiley & Sons. This book was released on 2019-03-18 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential guide on high dimensional multivariate time series including all the latest topics from one of the leading experts in the field Following the highly successful and much lauded book, Time Series Analysis—Univariate and Multivariate Methods, this new work by William W.S. Wei focuses on high dimensional multivariate time series, and is illustrated with numerous high dimensional empirical time series. Beginning with the fundamentalconcepts and issues of multivariate time series analysis,this book covers many topics that are not found in general multivariate time series books. Some of these are repeated measurements, space-time series modelling, and dimension reduction. The book also looks at vector time series models, multivariate time series regression models, and principle component analysis of multivariate time series. Additionally, it provides readers with information on factor analysis of multivariate time series, multivariate GARCH models, and multivariate spectral analysis of time series. With the development of computers and the internet, we have increased potential for data exploration. In the next few years, dimension will become a more serious problem. Multivariate Time Series Analysis and its Applications provides some initial solutions, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by bestselling author and leading expert in the field Covers topics not yet explored in current multivariate books Features classroom tested material Written specifically for time series courses Multivariate Time Series Analysis and its Applications is designed for an advanced time series analysis course. It is a must-have for anyone studying time series analysis and is also relevant for students in economics, biostatistics, and engineering.
