Time-series forecasting /
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| Author / Creator: | Chatfield, Christopher. |
|---|---|
| Imprint: | Boca Raton : Chapman & Hall/CRC, c2001. |
| Description: | x, 267 p. : ill. ; 24 cm. |
| Language: | English |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/4370754 |
Table of Contents:
- Preface
- Abbreviations and Notation
- 1. Introduction
- 1.1. Types of forecasting method
- 1.2. Some preliminary questions
- 1.3. The dangers of extrapolation
- 1.4. Are forecasts genuinely out-of-sample?
- 1.5. Brief overview of relevant literature
- 2. Basics of Time-Series Analysis
- 2.1. Different types of time series
- 2.2. Objectives of time-series analysis
- 2.3. Simple descriptive techniques
- 2.4. Stationary stochastic processes
- 2.5. Some classes of univariate time-series model
- 2.6. The correlogram
- 3. Univariate Time-Series Modelling
- 3.1. ARIMA models and related topics
- 3.2. State space models
- 3.3. Growth curve models
- 3.4. Non-linear models
- 3.5. Time-series model building
- 4. Univariate Forecasting Methods
- 4.1. The prediction problem
- 4.2. Model-based forecasting
- 4.3. Ad hoc forecasting methods
- 4.4. Some interrelationships and combinations
- 5. Multivariate Forecasting Methods
- 5.1. Introduction
- 5.2. Single-equation models
- 5.3. Vector AR and ARMA models
- 5.4. Cointegration
- 5.5. Econometric models
- 5.6. Other approaches
- 5.7. Some relationships between models
- 6. A Comparative Assessment of Forecasting Methods
- 6.1. Introduction
- 6.2. Criteria for choosing a forecasting method
- 6.3. Measuring forecast accuracy
- 6.4. Forecasting competitions and case studies
- 6.5. Choosing an appropriate forecasting method
- 6.6. Summary
- 7. Calculating Interval Forecasts
- 7.1. Introduction
- 7.2. Notation
- 7.3. The need for different approaches
- 7.4. Expected mean square prediction error
- 7.5. Procedures for calculating P.I.s
- 7.6. A comparative assessment
- 7.7. Why are P.I.s too narrow?
- 7.8. An example
- 7.9. Summary and recommendations
- 8. Model Uncertainty and Forecast Accuracy
- 8.1. Introduction to model uncertainty
- 8.2. Model building and data dredging
- 8.3. Examples
- 8.4. Inference after model selection: Some findings
- 8.5. Coping with model uncertainty
- 8.6. Summary and discussion
- References
- Index
