BMA weights as a function of leads (months) for four selected

Predicting geological interfaces using stacking ensemble learning

The seasonal variability of future evapotranspiration over China

Box‐Cox transformation parameter λ as function of the lead time (a

Water, Free Full-Text

Hanpei ZHANG, Research Assistant, Master of Atmospheric Science, University of Hawaiʻi at Mānoa, Hawaii, UH Manoa, Department of Meteorology

BMA weights as a function of leads (months) for four selected

Schematic structure of the BMA method for integrating all involved

Bayesian model averaging weights (equation 8) for the four

Transitions of the value of the BMA weight of ensemble member AVN

Pao-Shin CHU, University of Hawaiʻi at Mānoa, Hawaii, UH Manoa, Department of Meteorology

Remote Sensing, Free Full-Text