Unmasking the Theta Method

By Rob J Hyndman, B. Billah. 2003

169 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Statistical Learning Theory

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Citations in the corpus

Forecasting Across Time Series Databases using Long Short-Term Memory Networks on Groups of Similar Series (2017, methodology): “L G ] 9 O ct 2 01 7 damped trend exponential smoothing, and none of the methods was able to outperform the Theta method, which is equivalent to simple exponential smoothing with drift (Hyndman and Billah, 2003).”
Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors (2018, methodology): “Hyndman and Billah (2003) have proven that classic Theta is equal to SES with a drift equal to the half of the slope of the linear trend.”
Automatic Time Series Forecasting: The forecast Package for R (2008, background): “2000). Hyndman and Billah (2003) showed that these were equivalent to a special case of simple exponential smoothing with drift.”
Meta-learning for time series forecasting and forecast combination (2010, methodology): “Here, it is employed using formulas given by [23].”
25 years of time series forecasting (2006, methodology): “Hyndman & Billah (2003) showed that this method was also equivalent to Assimakopoulos & Nikolopoulos’s (2000) “Theta method” when the drift parameter is set to half the slope of a linear trend fitted to the data.”
25 Years of IIF Time Series Forecasting: A Selective Review (2005, methodology): “Hyndman & Billah (2003) showed that this method was also equivalent to Assimakopoulos & Nikolopoulos’s (2000) “Theta method” when the drift parameter is set to half the slope of a linear trend fitted to the data.”
'Horses for Courses' in demand forecasting (2014, methodology): “An analysis of the results suggested that SES with drift - a simplification of the Theta method (Assimakopoulos and Nikolopoulos, 2000) as proposed by Hyndman and Billah (2003) - provided the most accurate forecasts compared to any other smoothing method for every horizon.”
Forecasting: theory and practice (2020, methodology): “shown by Hyndman and Billah (2003) that the theta method can represent simple exponential smoothing”
The inventory performance of forecasting methods: Evidence from the M3 competition data (2019, methodology): “Hyndman and Billah (2003) and Fiorucci et al. (2016) showed that the standard version of Theta method that was applied at the M3-Competition is mathematically equivalent to SES with drift.”
Fathoming the theta method for a unit root process (2014, methodology): “Our approach thus includes the ARIMA(0,1,1) model used by Hyndman and Billah (2003) as a special case.”
Electricity price forecasting: A review of the state-of-the-art with a look into the future (2014, background): “Hyndman and Billah (2003) demonstrate that it is equivalent to simple exponential smoothing with drift, where the drift is half the value of the slope of a linear regression fitted to the data.”
Another look at measures of forecast accuracy (2006, methodology): “Hyndman and Billah (2003) demonstrated that this method is equivalent to simple exponential smoothing (SES) with drift where the drift is half the value of the slope of a linear regression fitted to the data.”