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Report NEP-FOR-2025-02-03
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:
- Joseph Nyangon & Ruth Akintunde, 2024, "Anomaly Detection in California Electricity Price Forecasting: Enhancing Accuracy and Reliability Using Principal Component Analysis," Papers, arXiv.org, number 2412.07787, Nov.
- Tomasz Serafin & Bartosz Uniejewski, 2024, "Ranking probabilistic forecasting models with different loss functions," Papers, arXiv.org, number 2411.17743, Nov.
- Jimmy Cheung & Smruthi Rangarajan & Amelia Maddocks & Xizhe Chen & Rohitash Chandra, 2024, "Quantile deep learning models for multi-step ahead time series prediction," Papers, arXiv.org, number 2411.15674, Nov.
- Worapree Maneesoonthorn & David T. Frazier & Gael M. Martin, 2024, "Probabilistic Predictions of Option Prices Using Multiple Sources of Data," Papers, arXiv.org, number 2412.00658, Nov.