Performance of state space and ARIMA models for consumer retail sales forecasting
By Patrícia Ramos, Nicolau Santos, Rui Diogo Rebelo. 2015
215 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/745b73d39bcefa4d244e78586b0f2fac075b467d
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
- Konstantinos Nikolopoulos
- Nikolaos Kourentzes
- Vassilios Assimakopoulos
- Spyros Makridakis
- Evangelos Spiliotis
- Christoph Bergmeir
In Statistics and Probability
- Konstantinos Nikolopoulos
- Vassilios Assimakopoulos
- Nikolaos Kourentzes
- Fotios Petropoulos
- Evangelos Spiliotis
- Spyros Makridakis
- Robert Fildes
- Christoph Bergmeir
Citations in the corpus
- Retail forecasting: Research and practice (2019, background): “Ramos et al. (2015) compared state space and ARIMA when forecasting monthly demand for women’s footwear for lead times 1 to 12 with little difference in accuracy.”
- Forecasting: theory and practice (2020, methodology): “These methods should only be used to forecast demand at higher aggregation levels or to forecast products with no promotional intensity (Ramos et al., 2015; Ramos and Oliveira, 2016).”