☆ 4.6 Article

Parameter-efficient deep probabilistic forecasting

INTERNATIONAL JOURNAL OF FORECASTING (2023)

Related references

Note: Only part of the references are listed.

Article Economics

Principles and algorithms for forecasting groups of time series: Locality and globality

Pablo Montero-Manso et al.

Summary: Global methods have shown surprising accuracy in forecasting large groups of heterogeneous time series. The complexity of local methods grows with the size of the set while it remains constant for global methods. Purposely naive algorithms derived from global methods show outstanding accuracy in empirical studies.

INTERNATIONAL JOURNAL OF FORECASTING (2021)

Add to Collection

Article Economics

Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Hansika Hewamalage et al.

Summary: Although Recurrent Neural Networks (RNNs) have shown competitive forecasting performance, they are not always superior to established statistical models such as exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA).

INTERNATIONAL JOURNAL OF FORECASTING (2021)

Add to Collection

Article Economics