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 |
| 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 |
| macOS binaries: | r-release: bbefkr_4.2.tgz, r-oldrel: bbefkr_4.2.tgz |
| Old sources: | bbefkr archive |
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