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This paper proposes a nonparametric residual error (NRE) model that effectively captures the statistical characteristics of raw residuals.
Improving probabilistic streamflow predictions through a ...
dl.acm.org › abs › j.envsoft.2024.105981
This paper proposes a nonparametric residual error (NRE) model that effectively captures the statistical characteristics of raw residuals. The NRE model employs ...
Improving Streamflow Predictions Through a Nonparametric Residual ...
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Aug 10, 2023 · This paper proposes a nonparametric residual error (NRE) model that effectively captures the statistical characteristics of raw residuals, ...
Improving Streamflow Predictions through a Nonparametric. 2. Residual Error Model ... probabilistic prediction method and residual models used in this work ...
Request PDF | On Feb 1, 2024, Jiyu Liang and others published Improving probabilistic streamflow predictions through a nonparametric residual error model ...
Improving probabilistic streamflow predictions through a nonparametric residual error model · Jiyu Liang · Shuguang Liu · Zhengzheng Zhou · Guihui Zhong · Yiwei Zhen.
Improving probabilistic streamflow predictions through a nonparametric residual error model ... error modeling for seamless subseasonal streamflow forecasting ...
Improving Streamflow Predictions Through a Nonparametric Residual Error Model. https://doi.org/10.2139/ssrn.4537478. Journal: 2023. Publisher: Elsevier BV.
Feb 3, 2017 · Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors.
PDF | On Oct 21, 2023, Zhong Guihui and others published code for paper "Improving Streamflow Predictions through a Nonparametric Residual Error Model ...