Preface
1 Introduction
2 Time-varying regression
- 2.1 Fitting time-varying regressions
- 2.2 Forecasting with a time-varying regression model
  - 2.2.1 The forecast package
  - 2.2.2 Summary
3 ARIMA Models
4 Exponential Smoothing Models
5 Testing forecast accuracy
- 5.1 Measures of forecast accuracy
- 5.2 Testing multiple models
  - 5.2.1 Example candidate model set for anchovy
6 Covariates
- 6.1 Multivariate linear regression with ARMA errors
  - 6.1.1 Example: anchovy
  - 6.1.2 MREG of first or second differences
7 Seasonality
References
Appendix
A Inputting data
B Downloading ICOADS covariates
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Fisheries Catch Forecasting

4.2 Simple ETS

Simple exponential smoothing uses this type of weighting that falls off exponentially and the objective to estimate the best weighting ( \(\alpha\) ):