Probabilistic forecasting of crop yields via quantile random forest and Epanechnikov Kernel function

Samuel Asante Gyamerah,Philip Ngare,Dennis Ikpe

Agricultural and Forest Meteorology（2020）

Cited 30|Views2

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Abstract

•Proposed a Epanechnikov kernel-based quantile random forest (QRF-E).•The proposed QRF-E can implement crop yield density forecasting.•PICP and PINAW are used to evaluate the performance of QRF-E.•The QRF-E model can improve the quality of prediction intervals.•The accuracy of the crop yield forecast is assessed using two cases of crop.

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Key words

Climate change,Crop yield forecasting,Quantile random forest,Kernel density estimation,Epanechnikov kernel,Prediction intervals

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