Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density
Abstract
This study examines the optimal selections of bandwidth and semi-metric for a functional partial linear model. Our proposed method begins by estimating the unknown error density using a kernel density estimator of residuals, where the regression function, consisting of parametric and nonparametric components, can be estimated by functional principal component and functional Nadayara-Watson estimators. The estimation accuracy of the regression...
Paper Details
Title
Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density
Published Date
Feb 24, 2020
Journal
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