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
Extreme values are often associated with tails of a cumulative distribution function, and the study of extreme values and their predictions is an important research topic in climate problems. Through a regression approach, we consider a scalar-on-function nonparametric regression to estimate and predict conditional quantiles, where the regression function can be estimated by the functional Nadaraya–Watson estimator. The accuracy of such an estimator crucially depends on the optimal selections...[Show more]
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|Source:||Journal of Multivariate Analysis|
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