A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data
A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data
作者
关键词
Extreme value prediction, Functional kernel regression, Kernel-form error density, Markov chain Monte Carlo
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