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bbemkr (version 1.5)
Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error
Description
Bayesian bandwidth estimation for Nadaraya-Watson type multivariate kernel regression with Gaussian error density
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Install
install.packages('bbemkr')
Monthly Downloads
98
Version
1.5
License
GPL (>= 2)
Maintainer
Han Lin Shang
Last Published
August 30th, 2011
Functions in bbemkr (1.5)
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LaplaceMetropolis
Laplace-Metropolis estimator of log marginal likelihood
logpriorh2
Prior of square bandwidths
np_gibbs
Estimating bandwidths of the regressors
warmup
Burn-in period
ker
Type of kernel function
kern
Calculate the R square value and mean square error as measures of goodness of fit
bbemkr-package
Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error assumption
data_y
Simulated response variable
cost2
Negative of log posterior associated with the error variance
loglikelihood
Calculate the log likelihood used in the Chib's (1995) log marginal density
nrr
Normal reference rule for estimating bandwidths
mcmcrecord
MCMC iterations
cov_chol
Calculate log marginal likeliood from MCMC output
cost
Negative of log posterior associated with the bandwidths
logdensity
Calculate an estimate of log posterior ordinate used in the log marginal density of Chib (1995).
NadarayaWatsonkernel
Nadaraya-Watson kernel estimator
xm
Values of true regression function
data_x
Simulated three-dimensional regressors
logpriors
Calculate the log prior used in the log marginal density of Chib (1995).