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Estimation of a functional single index model with dependent errors and unknown error density

Shang, Han Lin

Description

The problem of error density estimation for a functional single index model with dependent errors is studied. A Bayesian method is utilized to simultaneously estimate the bandwidths in the kernel-form error density and regression function, under an autoregressive error structure. For estimating both the regression function and error density, empirical studies show that the functional single index model gives improved estimation and prediction accuracies than any nonparametric functional...[Show more]

CollectionsANU Research Publications
Date published: 2018
Type: Journal article
URI: http://hdl.handle.net/1885/177001
Source: Communications in Statistics - Simulation and Computation
DOI: 10.1080/03610918.2018.1535068

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