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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.
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Package details |
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| Author | Han Lin Shang |
| Maintainer | Han Lin Shang <hanlin.shang@anu.edu.au> |
| License | GPL (>= 2) |
| Version | 4.2 |
| URL | https://sites.google.com/site/hanlinshangswebsite/ |
| Package repository | View on CRAN |
| Installation |
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