Forecasting: principles and practice

Forecasting: principles and practice
Author: Rob J Hyndman
Publisher: OTexts
Total Pages: 380
Release: 2018-05-08
Genre: Business & Economics
ISBN: 0987507117

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
Total Pages: 442
Release: 2021-05-31
Genre:
ISBN: 9780987507136

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
Total Pages: 292
Release: 2013-10
Genre: Business forecasting
ISBN: 9780987507105

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

Multiple Time Series Models

Multiple Time Series Models
Author: Patrick T. Brandt
Publisher: SAGE
Total Pages: 121
Release: 2007
Genre: Mathematics
ISBN: 1412906563

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.

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
Total Pages: 574
Release: 1990
Genre: Business & Economics
ISBN: 9780521405737

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.

Time Series and Dynamic Models

Time Series and Dynamic Models
Author: Christian Gourieroux
Publisher: Cambridge University Press
Total Pages: 692
Release: 1997
Genre: Business & Economics
ISBN: 9780521411462

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.

Regression and Time Series Model Selection

Regression and Time Series Model Selection
Author: Allan D. R. McQuarrie
Publisher: World Scientific
Total Pages: 479
Release: 1998
Genre: Mathematics
ISBN: 9812385452

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 for Business and Economic Forecasting

Time Series Models for Business and Economic Forecasting
Author: Philip Hans Franses
Publisher: Cambridge University Press
Total Pages: 421
Release: 2014-04-24
Genre: Business & Economics
ISBN: 1139952129

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
Total Pages: 473
Release: 2021-07-27
Genre: Mathematics
ISBN: 1498747043

• 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.

Bayesian Time Series Models

Bayesian Time Series Models
Author: David Barber
Publisher: Cambridge University Press
Total Pages: 432
Release: 2011-08-11
Genre: Computers
ISBN: 0521196760

The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.