Comparing seasonal components for structural time series models

By Tommaso Proietti. 2000

78 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Signal Processing

View Paper: https://www.semanticscholar.org/paper/447309fe0b39226b4adf4d8afaa979d3fec0c1e3

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

1. J. De Gooijer
2. Rob J Hyndman
3. Alysha M. De Livera
4. Ralph D. Snyder
5. Fotios Petropoulos
6. George Athanasopoulos
7. Nikolaos Kourentzes
8. Konstantinos Nikolopoulos

In Signal Processing

1. Rob J Hyndman
2. J. De Gooijer
3. Ralph D. Snyder
4. Alysha M. De Livera
5. James W. Taylor
6. Fotios Petropoulos
7. George Athanasopoulos
8. Spyros Makridakis

Citations in the corpus

• 25 Years of IIF Time Series Forecasting: A Selective Review (2005, background): “Proietti (2000) discussed several variations on the BSM and compared their properties and evaluated the resulting forecasts.”
• 25 years of time series forecasting (2006, background): “Proietti (2000) discussed several variations on the BSM and compared their properties and evaluated the resulting forecasts.”
• EXPONENTIAL SMOOTHING: THE STATE OF THE ART, PART II (2006, unknown): “For the trend and seasonal versions of exponential smoothing, the MSOE models are complex, as demonstrated in Proietti (1998, 2000), who gives examples of models that are equivalent to linear versions of exponential smoothing.”
• Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011, methodology): “A TBATS model should be distinguished from two other related (Proietti 2000) multiple source of error seasonal formulations presented by Hannan, Terrel, and Tuckwell (1970) and Harvey (1989).”