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bbemkr (version 1.4)

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

1.4

License

GPL (>= 2)

Maintainer

Han Lin Shang

Last Published

August 10th, 2011

Functions in bbemkr (1.4)

logpriors

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

Simulated three-dimensional regressors
loglikelihood

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

Nadaraya-Watson kernel estimator
kern

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

Values of true regression function
logpriorh2

Prior of square bandwidths
ker

Type of kernel function
data_y

Simulated response variable
np_gibbs

Estimating bandwidths of the regressors
bbemkr-package

Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error assumption
warmup

Burn-in period
cost2

Negative of log posterior associated with the error variance
logdensity

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

Normal reference rule for estimating bandwidths
mcmcrecord

MCMC iterations
cost

Negative of log posterior associated with the bandwidths