Estimating optimal bandwidths for the regression mean function approximated by the functional Nadaraya-Watson estimator and the error density approximated by a kernel density of residuals simultaneously in a scalar-on-function regression. As a by-product of Markov chain Monte Carlo, the optimal choice of semi-metric is selected based on largest marginal likelihood.
|Author||Han Lin Shang|
|Maintainer||Han Lin Shang <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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