bbefkr: Bayesian bandwidth estimation and semi-metric selection for the functional kernel regression with unknown error density

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.

Version: 4.2
Depends: R (≥ 3.0.3), splines
Published: 2014-04-29
Author: Han Lin Shang
Maintainer: Han Lin Shang <hanlin.shang at anu.edu.au>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://sites.google.com/site/hanlinshangswebsite/
NeedsCompilation: no
Citation: bbefkr citation info
Materials: ChangeLog
CRAN checks: bbefkr results

Downloads:

Reference manual: bbefkr.pdf
Vignettes: The bbefkr Package
Package source: bbefkr_4.2.tar.gz
Windows binaries: r-devel: bbefkr_4.2.zip, r-release: bbefkr_4.2.zip, r-oldrel: bbefkr_4.2.zip
OS X Mavericks binaries: r-release: bbefkr_4.2.tgz, r-oldrel: bbefkr_4.2.tgz
Old sources: bbefkr archive

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