Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density

24 Feb 2020 Shang Han Lin

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... (read more)

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