A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting

By N. Arunraj, Diane Ahrens. 2015

179 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/dd536ed9cf41cfc730f46aabc95f59bce5df4d19

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Christoph Bergmeir
2. Feng Li
3. John E. Boylan
4. Robert Fildes
5. Fotios Petropoulos
6. Ricardo J. Bessa
7. Florian Ziel

In Management Science and Operations Research

1. Fotios Petropoulos
2. Rob J Hyndman
3. Konstantinos Nikolopoulos
4. Nikolaos Kourentzes
5. Vassilios Assimakopoulos
6. Spyros Makridakis
7. Evangelos Spiliotis
8. Christoph Bergmeir

Citations in the corpus

• Forecasting: theory and practice (2020, background): “Arunraj and Ahrens (2015) proposed a SARIMAX model to forecast daily sales of fresh produce.”
• Food Security, Safety, and Sustainability—Getting the Trade-Offs Right (2020, background): “Could greater use of predictive models, machine learning, neural networks and expert systems (artificial intelligence or AI) enable the food business operators, to predict the demand for food? Could fine-tuning the supply operations and demand forecasts, minimize stock-outs, and food waste? By using”
• Retail forecasting: Research and practice (2019, background): “Arunraj and Ahrens (2015) developed a seasonal autoregressive integrated moving average with external variables (SARIMAX) model”