Forecasting: principles and practice
Forecasting: principles and practice

Author: Rob J Hyndman

Publisher: OTexts

Published: 2018-05-08

Total Pages: 380

ISBN-13: 0987507117

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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.

Forecasting
Forecasting

Author: Rob J Hyndman

Publisher: Otexts

Published: 2021-05-31

Total Pages: 442

ISBN-13: 9780987507136

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Forecasting is required in many situations. Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. 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. Examples use R with many data sets taken from the authors' own consulting experience. In this third edition, all chapters have been updated to cover the latest research and forecasting methods. One new chapter has been added on time series features. The latest version of the book is freely available online at http: //OTexts.com/fpp3.

Forecasting
Forecasting

Author: Rob J. Hyndman

Publisher: Otexts

Published: 2013-10

Total Pages: 292

ISBN-13: 9780987507105

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"A comprehensive introduction to the latest forecasting methods using R. Learn to improve your forecast accuracy using dozens of real data examples." --cover.

Time Series and Dynamic Models
Time Series and Dynamic Models

Author: Christian Gourieroux

Publisher: Cambridge University Press

Published: 1997

Total Pages: 692

ISBN-13: 9780521411462

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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.

Forecasting, Structural Time Series Models and the Kalman Filter
Forecasting, Structural Time Series Models and the Kalman Filter

Author: Andrew C. Harvey

Publisher: Cambridge University Press

Published: 1990

Total Pages: 574

ISBN-13: 9780521405737

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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.

Regression and Time Series Model Selection
Regression and Time Series Model Selection

Author: Allan D. R. McQuarrie

Publisher: World Scientific

Published: 1998

Total Pages: 479

ISBN-13: 9812385452

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This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.

Time Series Models
Time Series Models

Author: Andrew C. Harvey

Publisher: Financial Times/Prentice Hall

Published: 1993

Total Pages: 308

ISBN-13: 9780745012001

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A companion volume to The Econometric Analysis of Time series, this book focuses on the estimation, testing and specification of dynamic models which are not based on any behavioural theory. It covers univariate and multivariate time series and emphasizes autoregressive moving-average processes.

Multiple Time Series Models
Multiple Time Series Models

Author: Patrick T. Brandt

Publisher: SAGE

Published: 2007

Total Pages: 121

ISBN-13: 1412906563

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Many analyses of time series data involve multiple, related variables. Modeling Multiple Time Series presents many specification choices and special challenges. This book reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. The text focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. Specification, estimation, and inference using these models is discussed. The authors also review arguments for and against using multi-equation time series models. Two complete, worked examples show how VAR models can be employed. An appendix discusses software that can be used for multiple time series models and software code for replicating the examples is available. Key Features: * Offers a detailed comparison of different time series methods and approaches. * Includes a self-contained introduction to vector autoregression modeling. * Situates multiple time series modeling as a natural extension of commonly taught statistical models.

Time Series Models for Business and Economic Forecasting
Time Series Models for Business and Economic Forecasting

Author: Philip Hans Franses

Publisher: Cambridge University Press

Published: 2014-04-24

Total Pages: 421

ISBN-13: 1139952129

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With a new author team contributing decades of practical experience, this fully updated and thoroughly classroom-tested second edition textbook prepares students and practitioners to create effective forecasting models and master the techniques of time series analysis. Taking a practical and example-driven approach, this textbook summarises the most critical decisions, techniques and steps involved in creating forecasting models for business and economics. Students are led through the process with an entirely new set of carefully developed theoretical and practical exercises. Chapters examine the key features of economic time series, univariate time series analysis, trends, seasonality, aberrant observations, conditional heteroskedasticity and ARCH models, non-linearity and multivariate time series, making this a complete practical guide. Downloadable datasets are available online.

Time Series
Time Series

Author: Raquel Prado

Publisher: CRC Press

Published: 2021-07-27

Total Pages: 473

ISBN-13: 1498747043

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• 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.