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Report NEP-FOR-2023-04-10
This is the archive for NEP-FOR, a report on new working papers in the area of Forecasting. Rob J Hyndman issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-FOR
The following items were announced in this report:
- Jonathan Berrisch & Florian Ziel, 2023, "Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices," Papers, arXiv.org, number 2303.10019, Mar, revised Feb 2024.
- Thomas Wong & Mauricio Barahona, 2023, "Deep incremental learning models for financial temporal tabular datasets with distribution shifts," Papers, arXiv.org, number 2303.07925, Mar, revised Oct 2023.
- Jing Xie, 2023, "Identifying Optimal Indicators and Lag Terms for Nowcasting Models," IMF Working Papers, International Monetary Fund, number 2023/045, Mar.