A runoff probability density prediction method based on B-spline quantile regression and kernel density estimation

DOI10.1016/j.apm.2020.12.043zbMath1481.62019OpenAlexW3119704083MaRDI QIDQ823512

Jinhong Wan, Huiling Fan, Xiaohui Lei, Yao-Yao He

Publication date: 24 September 2021

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2020.12.043

zbMATH Keywords

B-spline quantile regressionprobability density predictionrunoff forecasting

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07)

Related Items (2)

CVaR-based optimization of environmental flow via the Markov lift of a mixed moving average process ⋮ Spline local basis methods for nonparametric density estimation

Uses Software

• gamair

Cites Work

• Modeling and forecasting river flows by means of filtered Poisson processes
• A mixed formulation of B-spline and a new class of spherical Hankel shape functions for modeling elastostatic problems
• Construction of beam elements considering von Kármán nonlinear strains using B-spline wavelet on the interval
• Regression Quantiles
• Prediction Intervals for Neural Networks via Nonlinear Regression
• Local Linear Additive Quantile Regression
• Strictly Proper Scoring Rules, Prediction, and Estimation
• Probabilistic Forecasts, Calibration and Sharpness
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