Abstract
A semi-parametric approach is developed to model nonlinear time series. This approach is used on hourly electricity load data, it considers the effect of temperature combined with those of time and day type. The temperature effect is modelled by nonparametric smoothing. An ARIMA model is used to model the serial correlation. An iterative backfitting algorithm is proposed for estimation. The post sample forecasting performance and comparative results show good potential of this approach.
| Original language | American English |
|---|---|
| State | Published - Nov 16 2005 |
| Event | INFORMS Annual Meeting - Phoenix, AZ Duration: Oct 14 2012 → … |
Conference
| Conference | INFORMS Annual Meeting |
|---|---|
| Period | 10/14/12 → … |
Disciplines
- Business
Keywords
- ARIMA
- Hourly electricity load data
- Nonlinear
- Nonparametric smoothing
- Semi-parametric approach
- Time series
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