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A nonparametric statistical procedure for ranking the overall performance of solar radiation models at multiple locations

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  • Stone, R.J.

Abstract

A nonparametric statistical procedure is presented as a solution to the problem of ranking the overall performance of solar radiation estimation models at multiple locations. The 11 steps of the computational procedure are demonstrated through the use of a worked example. The method not only allows models to be ranked based on their relative overall predictive accuracies but also enables the model tester to assess the level of statistical significance of the ranked order using critical z values of the normal probability distribution.

Suggested Citation

  • Stone, R.J., 1994. "A nonparametric statistical procedure for ranking the overall performance of solar radiation models at multiple locations," Energy, Elsevier, vol. 19(7), pages 765-769.
    • Handle: RePEc:eee:energy:v:19:y:1994:i:7:p:765-769
    DOI: 10.1016/0360-5442(94)90014-0
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    Cited by:

    1. Sharafi, Saeed & Nahvinia, Mohammad Javad, 2024. "Sustainability insights: Enhancing rainfed wheat and barley yield prediction in arid regions," Agricultural Water Management, Elsevier, vol. 299(C).
    2. de Simón-Martín, Miguel & Alonso-Tristán, Cristina & Díez-Mediavilla, Montserrat, 2017. "Diffuse solar irradiance estimation on building's façades: Review, classification and benchmarking of 30 models under all sky conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 783-802.
    3. Ali Mokhtar & Nadhir Al-Ansari & Wessam El-Ssawy & Renata Graf & Pouya Aghelpour & Hongming He & Salma M. Hafez & Mohamed Abuarab, 2023. "Prediction of Irrigation Water Requirements for Green Beans-Based Machine Learning Algorithm Models in Arid Region," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1557-1580, March.
    4. Gueymard, Christian A., 2014. "A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1024-1034.

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