Combination of long term and short term forecasts, with application to tourism demand forecasting
By Robert Andrawis, Amir F. Atiya, Hisham El-Shishiny. 2011
166 citations recorded by the source corpus.
Subfields: Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/34c90d2f806bc4b79be2bfe8cdb4a192e9d6ad46
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Fotios Petropoulos
- Rob J Hyndman
- Nikolaos Kourentzes
- George Athanasopoulos
- Spyros Makridakis
- Amir F. Atiya
- Konstantinos Nikolopoulos
- Haiyan Song
Citations in the corpus
- A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2011, result): “This is consistent with much of the findings in forecast combination literature, e.g. (Andrawis et al., 2011; Clemen, 1989; Timmermann, 2006; Andrawis et al., 2010) • The relative performance and ranking of the different strategies is persistent.”
- Improving forecasting by estimating time series structural components across multiple frequencies (2014, methodology): “Previous studies have tackled this issue by seasonally adjusting the original data (for example, Andrawis et al., 2011), and thus forcing a deterministic seasonality, which may be inappropriate, as well as requiring its characterisation between additive or multiplicative. This shift, from combining ”
- New developments in tourism and hotel demand modeling and forecasting (2017, background): “Andrawis et al. (2011) later combined the forecasts derived from tourism demand data to capture information of time series with different frequencies.”
- Forecasting in social settings: The state of the art (2020, background): “Current approaches to forecast combinations include, among others, combinations based on information criteria (Kolassa, 2011), the use of multiple temporal aggregation levels (Andrawis et al., 2011; Kourentzes et al., 2014; Athanasopoulos et al., 2017), bootstrapping for time series forecasting (”
- Forecasting with temporal hierarchies (2017, background): “As we argue above, the forecasts at different aggregation levels can support different managerial decisions and may not be reconciled.”
- An empirical comparison of alternate schemes for combining electricity spot price forecasts (2013, unknown): “Forecast averaging has become so popular, with so many different ways to combine forecasts, that Andrawis et al. (2011) suggest to use hierarchical forecast combinations, i.e. combining combined forecasts.”