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

Shang, Hanlin

Description

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 function and error density crucially depends on the...[Show more]

CollectionsANU Research Publications
Date published: 2020-03-03
Type: Journal article
URI: http://hdl.handle.net/1885/205795
Source: Journal of Applied Statistics
DOI: 10.1080/02664763.2020.1736527
Access Rights: Open Access

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