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bbemkr (version 1.6)

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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Version

Install

install.packages('bbemkr')

Monthly Downloads

19

Version

1.6

License

GPL (>= 2)

Maintainer

Han Lin Shang

Last Published

December 17th, 2013

Functions in bbemkr (1.6)

warmup_gaussian

Burn-in period
mcmcrecord_admkr

MCMC iterations
cost_gaussian

Negative of log posterior associated with the bandwidths
logpriorh2

Prior of square bandwidths
cov_chol_admkr

Calculate log marginal likelihood from MCMC output
xm

Values of true regression function
warmup_admkr

Burn-in period
cost2_gaussian

Negative of log posterior associated with the error variance
gibbs_admkr_nw

Estimating bandwidths of the regressors
data_x

Simulated three-dimensional regressors
loglikelihood_admkr

Calculate the log likelihood used in the Chib's (1995) log marginal density
gibbs_admkr_erro

Estimating bandwidth of the kernel-form error density
logdensity_gaussian

Calculate an estimate of log posterior ordinate used in the log marginal density of Chib (1995).
logpriors_gaussian

Calculate the log prior used in the log marginal density of Chib (1995).
np_gibbs

Estimating bandwidths of the regressors
cov_chol

Calculate log marginal likeliood from MCMC output
LaplaceMetropolis_admkr

Laplace-Metropolis estimator of log marginal likelihood
NadarayaWatsonkernel

Nadaraya-Watson kernel estimator
data_ynorm

Simulated response variable
kern

Calculate the R square value and mean square error as measures of goodness of fit
logpriors_admkr

Calculate the log prior used in the log marginal density of Chib (1995).
mcmcrecord_gaussian

MCMC iterations
cost_admkr

Negative of log posterior associated with the bandwidths
logdensity_admkr

Calculate an estimate of log posterior ordinate used in the log marginal density of Chib (1995).
nrr

Normal reference rule for estimating bandwidths
LaplaceMetropolis_gaussian

Laplace-Metropolis estimator of log marginal likelihood
ker

Type of kernel function
bbemkr-package

Bayesian bandwidth estimation for multivariate kernel regression
data_yt

Simulated response variable
loglikelihood_gaussian

Calculate the log likelihood used in the Chib's (1995) log marginal density