Hierarchical forecasting: issues and use guidelines

By G. Fliedner. 2001

88 citations recorded by the source corpus.

Subfields: Management Information Systems, Management Science and Operations Research

How researchers see this paper

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

In Management Information Systems

1. George Athanasopoulos
2. Rob J Hyndman
3. Konstantinos Nikolopoulos
4. Vassilios Assimakopoulos

In Management Science and Operations Research

1. Rob J Hyndman
2. Konstantinos Nikolopoulos
3. George Athanasopoulos
4. Vassilios Assimakopoulos
5. Han Lin Shang
6. Fotios Petropoulos
7. R. Ahmed
8. Evangelos Spiliotis

Citations in the corpus

• Optimal combination forecasts for hierarchical time series (2011, background): “Gross and Sohl (1990) discuss several possible ways of choosing these proportions. The bottom-up method involves forecasting each of the disaggregated series at the lowest level of the hierarchy, and then using simple aggregation to obtain forecasts at higher levels of the hierarchy. In practice, ma”
• Theta intelligent forecasting information system (2003, background): “…in which such an integration of decision support with intelligent features could generate critical advantages for corporate users (see for example Fliedner, 2001; Flores and Pearce, 2000; Adya et al., 2000; Spedding and Chan, 2000; Aiken, 1999; Lemos and Porto, 1998; Liu and Ridway, 1995;…”
• Exploiting big data in time series forecasting: A cross-sectional approach (2015, unknown): “One possible approach to overcome this issue is to exploit the hierarchical structure of a data set, if there is one [7].”