Forecasting: principles and practice

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Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.12/5 ( 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.

Forecasting, Structural Time Series Models and the Kalman Filter

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Publisher : Cambridge University Press
ISBN 13 : 9780521405737
Total Pages : 574 pages
Book Rating : 4.34/5 ( 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.

Time Series

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Publisher : CRC Press
ISBN 13 : 1420093363
Total Pages : 375 pages
Book Rating : 4.60/5 ( 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 2010-05-21 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.

Multivariate Tests for Time Series Models

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Publisher : SAGE
ISBN 13 : 9780803954403
Total Pages : 116 pages
Book Rating : 4.09/5 ( download)

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Book Synopsis Multivariate Tests for Time Series Models by : Jeff B. Cromwell

Download or read book Multivariate Tests for Time Series Models written by Jeff B. Cromwell and published by SAGE. This book was released on 1994 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests.

Time Series Models

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Publisher : Financial Times/Prentice Hall
ISBN 13 : 9780745012001
Total Pages : 308 pages
Book Rating : 4.00/5 ( download)

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Book Synopsis Time Series Models by : Andrew C. Harvey

Download or read book Time Series Models written by Andrew C. Harvey and published by Financial Times/Prentice Hall. This book was released on 1993 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Time Series

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Publisher : CRC Press
ISBN 13 : 1498747043
Total Pages : 473 pages
Book Rating : 4.42/5 ( 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.

Bayesian Time Series Models

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Publisher : Cambridge University Press
ISBN 13 : 0521196760
Total Pages : 432 pages
Book Rating : 4.65/5 ( download)

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Book Synopsis Bayesian Time Series Models by : David Barber

Download or read book Bayesian Time Series Models written by David Barber and published by Cambridge University Press. This book was released on 2011-08-11 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first unified treatment of time series modelling techniques spanning machine learning, statistics, engineering and computer science.

Time Series Models for Business and Economic Forecasting

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Publisher : Cambridge University Press
ISBN 13 : 1139952129
Total Pages : 421 pages
Book Rating : 4.25/5 ( download)

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Book Synopsis Time Series Models for Business and Economic Forecasting by : Philip Hans Franses

Download or read book Time Series Models for Business and Economic Forecasting written by Philip Hans Franses and published by Cambridge University Press. This book was released on 2014-04-24 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multiple Time Series Models

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Publisher : SAGE
ISBN 13 : 1412906563
Total Pages : 121 pages
Book Rating : 4.62/5 ( download)

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Book Synopsis Multiple Time Series Models by : Patrick T. Brandt

Download or read book Multiple Time Series Models written by Patrick T. Brandt and published by SAGE. This book was released on 2007 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and Dynamic Models

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Publisher : Cambridge University Press
ISBN 13 : 9780521411462
Total Pages : 692 pages
Book Rating : 4.67/5 ( 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.