Time Series And Dynamic Models

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Time Series and Dynamic Models

Author : Christian Gourieroux
Publisher : Cambridge University Press
ISBN 13 : 9780521411462
Total Pages : 692 pages
Book Rating : 4.4/5 (114 download)

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Book Synopsis Time Series and Dynamic Models by : Christian Gourieroux

Download or read book Time Series and Dynamic Models written by Christian Gourieroux and published by Cambridge University Press. This book was released on 1997 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close attention it pays to economic models and phenomena throughout. The coverage represents a major reference tool for graduate students, researchers and applied economists. The book is divided into four sections. Section one gives a detailed treatment of classical seasonal adjustment or smoothing methods. Section two provides a thorough coverage of various mathematical tools. Section three is the heart of the book, and is devoted to a range of important topics including causality, exogeneity shocks, multipliers, cointegration and fractionally integrated models. The final section describes the main contribution of filtering and smoothing theory to time series econometric problems.

Time Series and Dynamic Models

Author : Christian Gourieroux
Publisher : Cambridge University Press
ISBN 13 : 0521411467
Total Pages : 686 pages
Book Rating : 4.5/5 (214 download)

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Book Synopsis Time Series and Dynamic Models by : Christian Gourieroux

Download or read book Time Series and Dynamic Models written by Christian Gourieroux and published by Cambridge University Press. This book was released on 1997 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book Christian Gourieroux and Alain Monfort provide an up-to-date and comprehensive analysis of modern time series econometrics. They have succeeded in synthesising in an organised and integrated way a broad and diverse literature. While the book does not assume a deep knowledge of economics, one of its most attractive features is the close attention it pays to economic models and phenomena throughout. The coverage represents a major reference tool for graduate students, researchers and applied economists. The book is divided into four sections. Section one gives a detailed treatment of classical seasonal adjustment or smoothing methods. Section two provides a thorough coverage of various mathematical tools. Section three is the heart of the book, and is devoted to a range of important topics including causality, exogeneity shocks, multipliers, cointegration and fractionally integrated models. The final section describes the main contribution of filtering and smoothing theory to time series econometric problems.

Bayesian Forecasting and Dynamic Models

Author : Mike West
Publisher : Springer Science & Business Media
ISBN 13 : 1475793650
Total Pages : 720 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Bayesian Forecasting and Dynamic Models by : Mike West

Download or read book Bayesian Forecasting and Dynamic Models written by Mike West and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.

Introduction to Time Series Analysis

Author : Mark Pickup
Publisher : SAGE Publications
ISBN 13 : 1483313115
Total Pages : 233 pages
Book Rating : 4.4/5 (833 download)

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Book Synopsis Introduction to Time Series Analysis by : Mark Pickup

Download or read book Introduction to Time Series Analysis written by Mark Pickup and published by SAGE Publications. This book was released on 2014-10-15 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University

Forecasting: principles and practice

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis Forecasting: principles and practice by : Rob J Hyndman

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Geodetic Time Series Analysis in Earth Sciences

Author : Jean-Philippe Montillet
Publisher : Springer
ISBN 13 : 3030217183
Total Pages : 422 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Geodetic Time Series Analysis in Earth Sciences by : Jean-Philippe Montillet

Download or read book Geodetic Time Series Analysis in Earth Sciences written by Jean-Philippe Montillet and published by Springer. This book was released on 2019-08-16 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an essential appraisal of the recent advances in technologies, mathematical models and computational software used by those working with geodetic data. It explains the latest methods in processing and analyzing geodetic time series data from various space missions (i.e. GNSS, GRACE) and other technologies (i.e. tide gauges), using the most recent mathematical models. The book provides practical examples of how to apply these models to estimate seal level rise as well as rapid and evolving land motion changes due to gravity (ice sheet loss) and earthquakes respectively. It also provides a necessary overview of geodetic software and where to obtain them.

Dynamic Linear Models with R

Author : Giovanni Petris
Publisher : Springer Science & Business Media
ISBN 13 : 0387772383
Total Pages : 258 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Dynamic Linear Models with R by : Giovanni Petris

Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

Time Series Models

Author : Manfred Deistler
Publisher : Springer Nature
ISBN 13 : 3031132130
Total Pages : 213 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Time Series Models by : Manfred Deistler

Download or read book Time Series Models written by Manfred Deistler and published by Springer Nature. This book was released on 2022-10-21 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.

Dynamic Models for Volatility and Heavy Tails

Author : Andrew C. Harvey
Publisher : Cambridge University Press
ISBN 13 : 1107328780
Total Pages : pages
Book Rating : 4.1/5 (73 download)

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Book Synopsis Dynamic Models for Volatility and Heavy Tails by : Andrew C. Harvey

Download or read book Dynamic Models for Volatility and Heavy Tails written by Andrew C. Harvey and published by Cambridge University Press. This book was released on 2013-04-22 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.

Time Series

Author : Raquel Prado
Publisher : CRC Press
ISBN 13 : 1498747043
Total Pages : 473 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Time Series by : Raquel Prado

Download or read book Time Series written by Raquel Prado and published by CRC Press. This book was released on 2021-07-27 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Expanded on aspects of core model theory and methodology. • Multiple new examples and exercises. • Detailed development of dynamic factor models. • Updated discussion and connections with recent and current research frontiers.

Time Series Analysis

Author : Henrik Madsen
Publisher : CRC Press
ISBN 13 : 1420059688
Total Pages : 390 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Time Series Analysis by : Henrik Madsen

Download or read book Time Series Analysis written by Henrik Madsen and published by CRC Press. This book was released on 2007-11-28 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the author presents theorems to highlight the most

Time Series Analysis for the Social Sciences

Author : Janet M. Box-Steffensmeier
Publisher : Cambridge University Press
ISBN 13 : 1316060500
Total Pages : 297 pages
Book Rating : 4.3/5 (16 download)

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Book Synopsis Time Series Analysis for the Social Sciences by : Janet M. Box-Steffensmeier

Download or read book Time Series Analysis for the Social Sciences written by Janet M. Box-Steffensmeier and published by Cambridge University Press. This book was released on 2014-12-22 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series, or longitudinal, data are ubiquitous in the social sciences. Unfortunately, analysts often treat the time series properties of their data as a nuisance rather than a substantively meaningful dynamic process to be modeled and interpreted. Time Series Analysis for the Social Sciences provides accessible, up-to-date instruction and examples of the core methods in time series econometrics. Janet M. Box-Steffensmeier, John R. Freeman, Jon C. Pevehouse and Matthew P. Hitt cover a wide range of topics including ARIMA models, time series regression, unit-root diagnosis, vector autoregressive models, error-correction models, intervention models, fractional integration, ARCH models, structural breaks, and forecasting. This book is aimed at researchers and graduate students who have taken at least one course in multivariate regression. Examples are drawn from several areas of social science, including political behavior, elections, international conflict, criminology, and comparative political economy.

Discrete-time Dynamic Models

Author : Ronald K. Pearson
Publisher : Oxford University Press
ISBN 13 : 0195352815
Total Pages : 481 pages
Book Rating : 4.1/5 (953 download)

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Book Synopsis Discrete-time Dynamic Models by : Ronald K. Pearson

Download or read book Discrete-time Dynamic Models written by Ronald K. Pearson and published by Oxford University Press. This book was released on 1999-12-02 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fueled by advances in computer technology, model-based approaches to the control of industrial processes are now widespread. While there is an enormous literature on modeling, the difficult first step of selecting an appropriate model structure has received almost no attention. This book fills the gap, providing practical insight into model selection for chemical processes and emphasizing structures suitable for control system design.

Forecasting, Structural Time Series Models and the Kalman Filter

Author : Andrew C. Harvey
Publisher : Cambridge University Press
ISBN 13 : 9780521405737
Total Pages : 574 pages
Book Rating : 4.4/5 (57 download)

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Book Synopsis Forecasting, Structural Time Series Models and the Kalman Filter by : Andrew C. Harvey

Download or read book Forecasting, Structural Time Series Models and the Kalman Filter written by Andrew C. Harvey and published by Cambridge University Press. This book was released on 1990 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: A synthesis of concepts and materials, that ordinarily appear separately in time series and econometrics literature, presents a comprehensive review of theoretical and applied concepts in modeling economic and social time series.

Introduction to Multiple Time Series Analysis

Author : Helmut Lütkepohl
Publisher : Springer Science & Business Media
ISBN 13 : 3662026910
Total Pages : 556 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Introduction to Multiple Time Series Analysis by : Helmut Lütkepohl

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 2013-04-17 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Time Series Analysis

Author : George E. P. Box
Publisher : John Wiley & Sons
ISBN 13 : 1118674928
Total Pages : 712 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Time Series Analysis by : George E. P. Box

Download or read book Time Series Analysis written by George E. P. Box and published by John Wiley & Sons. This book was released on 2015-05-29 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Fourth Edition "The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control." —Mathematical Reviews Bridging classical models and modern topics, the Fifth Edition of Time Series Analysis: Forecasting and Control maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the Fifth Edition continues to serve as one of the most influential and prominent works on the subject. Time Series Analysis: Forecasting and Control, Fifth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic models for time series and describes their use in five important areas of application: forecasting; determining the transfer function of a system; modeling the effects of intervention events; developing multivariate dynamic models; and designing simple control schemes. Along with these classical uses, the new edition covers modern topics with new features that include: A redesigned chapter on multivariate time series analysis with an expanded treatment of Vector Autoregressive, or VAR models, along with a discussion of the analytical tools needed for modeling vector time series An expanded chapter on special topics covering unit root testing, time-varying volatility models such as ARCH and GARCH, nonlinear time series models, and long memory models Numerous examples drawn from finance, economics, engineering, and other related fields The use of the publicly available R software for graphical illustrations and numerical calculations along with scripts that demonstrate the use of R for model building and forecasting Updates to literature references throughout and new end-of-chapter exercises Streamlined chapter introductions and revisions that update and enhance the exposition Time Series Analysis: Forecasting and Control, Fifth Edition is a valuable real-world reference for researchers and practitioners in time series analysis, econometrics, finance, and related fields. The book is also an excellent textbook for beginning graduate-level courses in advanced statistics, mathematics, economics, finance, engineering, and physics.

Applied Econometrics with R

Author : Christian Kleiber
Publisher : Springer Science & Business Media
ISBN 13 : 0387773185
Total Pages : 229 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Applied Econometrics with R by : Christian Kleiber

Download or read book Applied Econometrics with R written by Christian Kleiber and published by Springer Science & Business Media. This book was released on 2008-12-10 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.