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Forecasting with the Theta Method : Theory and Applications.
The first book to be published on the Theta method, outlining under what conditions the method outperforms other forecasting methods This book is the first to detail the Theta method of forecasting - one of the most difficult-to-beat forecasting benchmarks, which topped the biggest forecasting compe...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Newark :
John Wiley & Sons, Incorporated,
2018.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Nikolopoulos, Konstantinos (Kostas) | |
| 245 | 1 | 0 | |a Forecasting with the Theta Method : |b Theory and Applications. |
| 260 | |a Newark : |b John Wiley & Sons, Incorporated, |c 2018. | ||
| 300 | |a 1 online resource (201 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Title Page; Copyright; Contents; Author Biography; Preface; Part I Theory, Methods and Models; Chapter 1 The -legacy; 1.1 The Origins ... ; 1.1.1 The Quest for Causality; 1.2 The Original Concept: THETA as in THErmosTAt; 1.2.1 Background: A Decomposition Approach to Forecasting; 1.2.2 The Original Basic Model of the Theta Method; 1.2.3 How to Build and Forecast with the Basic Model; 1.2.4 SES with Drift; 1.2.5 The Exact Setup in the M3 Competition; 1.2.6 Implementing the Basic Version in Microsoft Excel; 1.2.7 The FutuRe is Written in R; 1.A Appendix | |
| 520 | |a The first book to be published on the Theta method, outlining under what conditions the method outperforms other forecasting methods This book is the first to detail the Theta method of forecasting - one of the most difficult-to-beat forecasting benchmarks, which topped the biggest forecasting competition in the world in 2000: the M3 competition. Written by two of the leading experts in the forecasting field, it illuminates the exact replication of the method and under what conditions the method outperforms other forecasting methods. Recent developments such as multivariate models are also included, as are a series of practical applications in finance, economics, and healthcare. The book also offers practical tools in MS Excel and guidance, as well as provisional access, for the use of R source code and respective packages. Forecasting with the Theta Method: Theory and Applications includes three main parts. The first part, titled Theory, Methods, Models & Applications details the new theory about the method. The second part, Applications & Performance in Forecasting Competitions, describes empirical results and simulations on the method. The last part roadmaps future research and also include contributions from another leading scholar of the method - Dr. Fotios Petropoulos.-First ever book to be published on the Theta Method -Explores new theory and exact conditions under which methods would outperform most forecasting benchmarks -Clearly written with practical applications -Employs R - open source code with all included implementations Forecasting with the Theta Method: Theory and Applications is a valuable tool for both academics and practitioners involved in forecasting and respective software development. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Business forecasting. | |
| 650 | 6 | |a Prévision commerciale. | |
| 650 | 7 | |a BUSINESS & ECONOMICS |x Statistics. |2 bisacsh | |
| 650 | 7 | |a Business forecasting |2 fast | |
| 700 | 1 | |a Thomakos, D. D. | |
| 758 | |i has work: |a Forecasting with the Theta method (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFtRjC6g7GT8JwV7xVQVfm |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Nikolopoulos, Konstantinos (Kostas). |t Forecasting with the Theta Method : Theory and Applications. |d Newark : John Wiley & Sons, Incorporated, ©2018 |z 9781119320760 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5630247 |z Texto completo |
| 880 | 8 | |6 505-00/(S |a 3.2 Selection of Trend Function and ExtensionsPart II Applications and Performance in Forecasting Competitions; Chapter 4 Empirical Applications with the θ-method; 4.1 Setting up the Analysis; 4.1.1 Sample Use, Evaluation Metrics, and Models/Methods Used; 4.1.2 Data; 4.2 Series CREDIT; 4.3 Series UNRATE; 4.4 Series EXPIMP; 4.5 Series TRADE; 4.6 Series JOBS; 4.7 Series FINANCE; 4.8 Summary of Empirical Findings; Chapter 5 Applications in Health Care; 5.1 Forecasting the Number of Dispensed Units of Branded and Generic Pharmaceuticals; 5.2 The Data; 5.2.1 Prescribed vs. Dispensed | |
| 880 | 8 | |6 505-00/(S |a 5.2.2 The Dataset5.3 Results for Branded; 5.4 Results for Generic; Part III The Future of the θ-method; Chapter 6 θ-Reflections from the Next Generation of Forecasters; 6.1 Design; 6.2 Seasonal Adjustment; 6.3 Optimizing the Theta Lines; 6.4 Adding a Third Theta Line; 6.5 Adding a Short-term Linear Trend Line; 6.6 Extrapolating Theta Lines; 6.7 Combination Weights; 6.8 A Robust Theta Method; 6.9 Applying Theta Method in R Statistical Software; Chapter 7 Conclusions and the Way Forward; References; Index; EULA | |
| 880 | 8 | |6 505-00/(S |a Chapter 2 From the From the -method to a -model2.1 Stochastic and Deterministic Trends and their DGPs; 2.2 The θ-method Applied to the Unit Root with Drift DGP; 2.2.1 Main Results; 2.2.2 Alternative Trend Functions and the Original θ-line Approach; 2.2.3 Implementing the θ-method under the Unit Root DGP; 2.3 The θ-method Applied to the Trend-stationary DGP; 2.3.1 Implementing the θ-method under the Trend-stationary DGP; 2.3.2 Is the AR(1)-forecast a θ-forecast; Chapter 3 The Multivariate θ-method; 3.1 The Bivariate θ-method for the Unit Root DGP | |
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