Approaches for multi-step density forecasts with application to aggregated wind power

DOI10.1214/09-AOAS320zbMath1202.62129arXiv1003.0996MaRDI QIDQ614143

Ada Lau, Patrick E. McSharry

Publication date: 27 December 2010

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1003.0996

zbMATH Keywords

exponential smoothingtruncated normal distributionnon-Gaussian time seriescontinuous ranked probability scoreARIMA-GARCH modellogistic transformation

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Monte Carlo methods (65C05)

Related Items (6)

Optimal resource distribution between protection and redundancy considering the time and uncertainties of attacks ⋮ Modeling and forecasting electricity spot prices: a functional data perspective ⋮ GARCH density and functional forecasts ⋮ Wind energy: forecasting challenges for its operational management ⋮ Spatiotemporal probabilistic wind vector forecasting over Saudi Arabia ⋮ Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-Term Forecasting of Wind Speed

Uses Software

• expsmooth
• FinTS

Cites Work

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