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

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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
Date of publication
2014-04-29 07:59:07
Maintainer
Han Lin Shang <hanlin.shang@anu.edu.au>
License
GPL (>= 2)
Version
4.2
URLs

View on CRAN

Man pages

bayMCMC_np_global
Bayesian bandwidth estimation for a functional nonparametric...
bayMCMC_np_local
Bayesian bandwidth estimation for a functional nonparametric...
bayMCMC_semi_global
Bayesian bandwidth estimation for a semi-functional partial...
bayMCMC_semi_local
Bayesian bandwidth estimation for a semi-functional partial...
bbefkr-package
Bayesian bandwidth estimation for the functional kernel...
error.den
Compute the probability density function and cumulative...
error.denadj
Compute the probability density function and cumulative...
funopare.kernel
Functional Nadaraya-Watson estimator
logdensity_admkr
Compute the marginal likelihood using Chib's (1995) method
loglikelihood_global_admkr
Compute the marginal likelihood using Chib's (1995) method
logpriorh2
Prior density of the squared bandwidth parameters
logpriors_admkr
Compute the marginal likelihood using Chib's (1995) method
SIF
Simulation inefficiency factor
simcurve_smooth_normerr
Simulated data set
simulate_error
Simulate errors
specurves
Spectroscopy tecator data
Xvar
Simulated real-valued predictors in the semi-functional...

Files in this package

bbefkr
bbefkr/inst
bbefkr/inst/CITATION
bbefkr/inst/doc
bbefkr/inst/doc/bbefkr.R
bbefkr/inst/doc/bbefkr.Rnw
bbefkr/inst/doc/bbefkr.pdf
bbefkr/NAMESPACE
bbefkr/CHANGELOG
bbefkr/GPL-2
bbefkr/data
bbefkr/data/tau_normerr.rda
bbefkr/data/protein.rda
bbefkr/data/Xvar.rda
bbefkr/data/simresp_semi_normerr.rda
bbefkr/data/tau_semierr.rda
bbefkr/data/simresp_np_normerr.rda
bbefkr/data/simcurve_smooth_normerr.rda
bbefkr/data/specurves.rda
bbefkr/data/moisture.rda
bbefkr/data/simcurve_rough_normerr.rda
bbefkr/data/fat.rda
bbefkr/R
bbefkr/R/error.denadj.R
bbefkr/R/simdiscretecomb.R
bbefkr/R/simskewbimodal.R
bbefkr/R/simbimodal.R
bbefkr/R/bayMCMC_np_local.R
bbefkr/R/simsepbimodal.R
bbefkr/R/simtrimodal.R
bbefkr/R/funopare.kernel.R
bbefkr/R/bayMCMC_semi_local.R
bbefkr/R/simulate_error.R
bbefkr/R/quadratic.R
bbefkr/R/semimetric.deriv.R
bbefkr/R/SIF.R
bbefkr/R/logdensity_admkr.R
bbefkr/R/error.den.R
bbefkr/R/simclaw.R
bbefkr/R/simasyclaw.R
bbefkr/R/error.cdfadj.R
bbefkr/R/bbefkr-internal.R
bbefkr/R/bayMCMC_np_global.R
bbefkr/R/loglikelihood_local_admkr.R
bbefkr/R/simstrongskew.R
bbefkr/R/simkurtotic.R
bbefkr/R/simasydoubleclaw.R
bbefkr/R/logpriors_admkr.R
bbefkr/R/symsolve.R
bbefkr/R/simsmoothcomb.R
bbefkr/R/simskewunimodal.R
bbefkr/R/simoutlier.R
bbefkr/R/logpriorh2.R
bbefkr/R/loglikelihood_global_admkr.R
bbefkr/R/simdoubleclaw.R
bbefkr/R/error.cdf.R
bbefkr/R/bayMCMC_semi_global.R
bbefkr/R/semimetric.pca.R
bbefkr/vignettes
bbefkr/vignettes/smoothcurves.pdf
bbefkr/vignettes/roughcurves.pdf
bbefkr/vignettes/spec.pdf
bbefkr/vignettes/Shang.bib
bbefkr/vignettes/bbefkr.Rnw
bbefkr/MD5
bbefkr/build
bbefkr/build/vignette.rds
bbefkr/DESCRIPTION
bbefkr/man
bbefkr/man/bayMCMC_np_local.Rd
bbefkr/man/SIF.Rd
bbefkr/man/logpriors_admkr.Rd
bbefkr/man/funopare.kernel.Rd
bbefkr/man/bayMCMC_semi_local.Rd
bbefkr/man/simcurve_smooth_normerr.Rd
bbefkr/man/bayMCMC_np_global.Rd
bbefkr/man/error.denadj.Rd
bbefkr/man/logdensity_admkr.Rd
bbefkr/man/simulate_error.Rd
bbefkr/man/loglikelihood_global_admkr.Rd
bbefkr/man/bayMCMC_semi_global.Rd
bbefkr/man/bbefkr-package.Rd
bbefkr/man/Xvar.Rd
bbefkr/man/error.den.Rd
bbefkr/man/logpriorh2.Rd
bbefkr/man/specurves.Rd
bbefkr/GPL-3