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Author : Jean-Marc Beguin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)
Download or read book Identification of a Mixed Autoregressive-moving Average Process written by Jean-Marc Beguin and published by . This book was released on 1979 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hlung-Wen Jack Penm
Publisher :
ISBN 13 :
Total Pages : 148 pages
Book Rating : 4.:/5 (154 download)
Download or read book Identification of Two-dimensional Autoregressive-moving Average Process written by Hlung-Wen Jack Penm and published by . This book was released on 19?? with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Norman Owen Speakman
Publisher :
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.:/5 (142 download)
Download or read book Autoregressive Moving-average (ARMA) Model Identification for Degenerate Time Series with Application to Maneuvering Target Tracking written by Norman Owen Speakman and published by . This book was released on 1985 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research was conducted in the general areas of time series analysis and stochastic realization. Results were then applied to the specific problem of tracking a highly maneuverable aircraft target. An algorithm was developed to identify the order and parameters of the minimum autoregressive moving-average (ARMA) model of a multi-variable system given the output autocorrelation sequence. Studies were also conducted in the area of degenerate time series modeling. It was found that degeneracy in vector-valued time series is caused by the presence of one or more deterministic relationships in the time series. ARMA models for degenerate time series can be identified by finding and extracting the deterministic relationships from the time series. The result is a reduced dimension atochastic model of the system, The model found will have fewer white noise inputs than outputs. An AR
Author : John Eatwell
Publisher : Palgrave Macmillan
ISBN 13 : 9780333495513
Total Pages : 325 pages
Book Rating : 4.4/5 (955 download)
Download or read book Time Series and Statistics written by John Eatwell and published by Palgrave Macmillan. This book was released on 1990-07-23 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : G. T. Wilson
Publisher :
ISBN 13 :
Total Pages : 35 pages
Book Rating : 4.:/5 (227 download)
Download or read book A Unified Approach to ARMA (Autoregressive-Moving Average) Model Identification and Preliminary Estimation written by G. T. Wilson and published by . This book was released on 1983 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper reviews several different methods for identifying the orders of autoregressive-moving average models for time series data. The case is made that these have a common basis, and that a unified approach may be found in the analysis of a matrix G, defined to be the covariance matrix of forecast values. The estimation of this matrix is considered, emphasis being placed on the use of high order autoregression to approximate the predictor coefficients. Statistical procedures are proposed for analyzing G, and identifying the model orders. A simulation example and three sets of real data are used to illustrate the procedure, which appears to be very useful as a tool for order identification and preliminary model estimation. (Author).
Author : ByoungSeon Choi
Publisher : Springer Science & Business Media
ISBN 13 : 1461397456
Total Pages : 211 pages
Book Rating : 4.4/5 (613 download)
Download or read book ARMA Model Identification written by ByoungSeon Choi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last two decades, considerable progress has been made in statistical time series analysis. The aim of this book is to present a survey of one of the most active areas in this field: the identification of autoregressive moving-average models, i.e., determining their orders. Readers are assumed to have already taken one course on time series analysis as might be offered in a graduate course, but otherwise this account is self-contained. The main topics covered include: Box-Jenkins' method, inverse autocorrelation functions, penalty function identification such as AIC, BIC techniques and Hannan and Quinn's method, instrumental regression, and a range of pattern identification methods. Rather than cover all the methods in detail, the emphasis is on exploring the fundamental ideas underlying them. Extensive references are given to the research literature and as a result, all those engaged in research in this subject will find this an invaluable aid to their work.
Author : Alasdair John Anderson MacCormick
Publisher :
ISBN 13 :
Total Pages : 242 pages
Book Rating : 4.:/5 (89 download)
Download or read book Investigation of the Behavior of Autocorrelation and Partial Autocorrelation Functions with Application to Identification of Autoregressive Moving Average Models in Time Series Analysis written by Alasdair John Anderson MacCormick and published by . This book was released on 1970 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book IDENTIFICATION OF PERIODIC AUTOREGRESSIVE MOVING AVERAGE MODELS. written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, identification of periodically varying orders of univariate Periodic Autoregressive Moving-Average (PARMA) processes is mainly studied. The identification of the varying orders of PARMA process is carried out by generalizing the well-known Box-Jenkins techniques to a seasonwise manner. The identification of pure periodic moving-average (PMA) and pure periodic autoregressive (PAR) models are considered only. For PARMA model identification, the Periodic Autocorrelation Function (PeACF) and Periodic Partial Autocorrelation Function (PePACF), which play the same role as their ARMA counterparts, are employed. For parameter estimation, which is considered only to refine model identification, the conditional least squares estimation (LSE) method is used which is applicable to PAR models. Estimation becomes very complicated, difficult and may give unsatisfactory results when a moving-average (MA) component exists in the model. On account of overcoming this difficulty, seasons following PMA processes are tried to be modeled as PAR processes with reasonable orders in order to employ LSE. Diagnostic checking, through residuals of the fitted model, is also performed stating its reasons and methods. The last part of the study demonstrates application of identification techniques through analysis of two seasonal hydrologic time series, which consist of average monthly streamflows. For this purpose, computer programs were developed specially for PARMA model identification.
Author : George G. Judge
Publisher : John Wiley & Sons
ISBN 13 : 047189530X
Total Pages : 1062 pages
Book Rating : 4.4/5 (718 download)
Download or read book The Theory and Practice of Econometrics written by George G. Judge and published by John Wiley & Sons. This book was released on 1991-01-16 with total page 1062 pages. Available in PDF, EPUB and Kindle. Book excerpt: This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
Author : Wayne A. Woodward
Publisher : CRC Press
ISBN 13 : 1498734316
Total Pages : 460 pages
Book Rating : 4.4/5 (987 download)
Download or read book Applied Time Series Analysis with R written by Wayne A. Woodward and published by CRC Press. This book was released on 2017-02-17 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis. Features Gives readers the ability to actually solve significant real-world problems Addresses many types of nonstationary time series and cutting-edge methodologies Promotes understanding of the data and associated models rather than viewing it as the output of a "black box" Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website. Over 150 exercises and extensive support for instructors The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with time-varying frequencies (TVF).
Author : Daniel Peña
Publisher : John Wiley & Sons
ISBN 13 : 1118031229
Total Pages : 494 pages
Book Rating : 4.1/5 (18 download)
Download or read book A Course in Time Series Analysis written by Daniel Peña and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.
Author : Lon-Mu Liu
Publisher :
ISBN 13 : 9780976505662
Total Pages : pages
Book Rating : 4.5/5 (56 download)
Download or read book Time Series Analysis and Forecasting written by Lon-Mu Liu and published by . This book was released on 2006-01-01 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : James D. Hamilton
Publisher : Princeton University Press
ISBN 13 : 0691218633
Total Pages : 820 pages
Book Rating : 4.6/5 (912 download)
Download or read book Time Series Analysis written by James D. Hamilton and published by Princeton University Press. This book was released on 2020-09-01 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative, self-contained overview of time series analysis for students and researchers The past decade has brought dramatic changes in the way that researchers analyze economic and financial time series. This textbook synthesizes these advances and makes them accessible to first-year graduate students. James Hamilton provides comprehensive treatments of important innovations such as vector autoregressions, generalized method of moments, the economic and statistical consequences of unit roots, time-varying variances, and nonlinear time series models. In addition, he presents basic tools for analyzing dynamic systems—including linear representations, autocovariance generating functions, spectral analysis, and the Kalman filter—in a way that integrates economic theory with the practical difficulties of analyzing and interpreting real-world data. Time Series Analysis fills an important need for a textbook that integrates economic theory, econometrics, and new results. This invaluable book starts from first principles and should be readily accessible to any beginning graduate student, while it is also intended to serve as a reference book for researchers.
Author : Guido Masarotto
Publisher :
ISBN 13 :
Total Pages : 10 pages
Book Rating : 4.:/5 (883 download)
Download or read book Robust Identification of Autoregressive Moving Average Models written by Guido Masarotto and published by . This book was released on 1987 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Marc S. Paolella
Publisher : John Wiley & Sons
ISBN 13 : 1119431905
Total Pages : 896 pages
Book Rating : 4.1/5 (194 download)
Download or read book Linear Models and Time-Series Analysis written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-12-17 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. Covers traditional time series analysis with new guidelines Provides access to cutting edge topics that are at the forefront of financial econometrics and industry Includes latest developments and topics such as financial returns data, notably also in a multivariate context Written by a leading expert in time series analysis Extensively classroom tested Includes a tutorial on SAS Supplemented with a companion website containing numerous Matlab programs Solutions to most exercises are provided in the book Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH is suitable for advanced masters students in statistics and quantitative finance, as well as doctoral students in economics and finance. It is also useful for quantitative financial practitioners in large financial institutions and smaller finance outlets.
Author : Terence C. Mills
Publisher : Cambridge University Press
ISBN 13 : 9780521405744
Total Pages : 392 pages
Book Rating : 4.4/5 (57 download)
Download or read book Time Series Techniques for Economists written by Terence C. Mills and published by Cambridge University Press. This book was released on 1990 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. In this book, Terence Mills not only brings together recent research at the frontiers of the subject, but also analyses the areas of most importance to applied economics. It is an up-to-date text which extends the basic techniques of analysis to cover the development of methods that can be used to analyse a wide range of economic problems. The book analyses three basic areas of time series analysis: univariate models, multivariate models, and non-linear models. In each case the basic theory is outlined and then extended to cover recent developments. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. This book clearly distinguishes itself from its competitors by emphasising the techniques of time series modelling rather than technical aspects such as estimation, and by the breadth of the models considered. It features many detailed real-world examples using a wide range of actual time series. It will be useful to econometricians and specialists in forecasting and finance and accessible to most practitioners in economics and the allied professions.
Author : Jonathan D. Cryer
Publisher : Springer Science & Business Media
ISBN 13 : 038775959X
Total Pages : 501 pages
Book Rating : 4.3/5 (877 download)
Download or read book Time Series Analysis written by Jonathan D. Cryer and published by Springer Science & Business Media. This book was released on 2008-03-06 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.
