| Type: | Package |
| Title: | Kernel Density Estimation with a Markov Chain Monte Carlo Sample |
| Version: | 0.0.1 |
| Date: | 2025-04-21 |
| Maintainer: | Juhee Lee <ljh988488@gmail.com> |
| Description: | Provides methods for selecting the optimal bandwidth in kernel density estimation for dependent samples, such as those generated by Markov chain Monte Carlo (MCMC). Implements a modified biased cross-validation (mBCV) approach that accounts for sample dependence, improving the accuracy of estimated density functions. |
| License: | GPL (≥ 3) |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp, methods |
| LinkingTo: | Rcpp, RcppArmadillo |
| LazyData: | true |
| RcppModules: | cKDEmodule |
| NeedsCompilation: | yes |
| RoxygenNote: | 7.3.2 |
| Packaged: | 2025-04-21 09:44:43 UTC; user |
| Author: | Juhee Lee [aut, cre], Hang J. Kim [aut], Young-Min Kim [aut] |
| Repository: | CRAN |
| Date/Publication: | 2025-04-24 07:30:01 UTC |
Internal S4 Class for Bandwidth Estimation
Description
An internal S4 class used in the implementation of kernel density bandwidth estimation using MCMC samples. This class is not intended to be used directly by package users.
Objects from the Class
Objects of this class are created internally by C++ functions exposed via Rcpp. End users should not create or manipulate instances of this class.
Slots
This class does not expose any user-accessible slots.
RCPP Implementation of the Library
Description
Value
No return value
Calculate Optimal Bandwidth in Kernel Density Estimation
Description
Calculate the optimal bandwidth for the kernel density estimator with a Markov chain Monte Carlo sample using modified biased cross-validation method.
Usage
mBCV(Y_in)
## S3 method for class 'mBCV_obj'
print(x, ...)
Arguments
Y_in |
data from which the estimate is to be computed. |
x |
object of class |
... |
further arguments passed to or from other methods. |
Value
mBCV returns a list of the following conmponents:
bw |
optimal bandwidth. |
IACT |
intergrated autocorrelation time. |
Y_in |
input data. |
Examples
res = mBCV(simMCMC)
den = density(res$Y_in, bw=res$bw)
hist(res$Y_in, xlim=range(den$x), freq=FALSE,
main="Histogram and Density Estimates", xlab="")
lines(den$x, den$y, col='blue', lwd=2)
Plot Kernel Density Result from mBCV_obj
Description
draw a histogram and density curve of the results.
Usage
## S3 method for class 'mBCV_obj'
plot(x, main=NULL, xlab="", ...)
Arguments
x |
|
main |
title of plot. |
xlab |
title for the x axis. |
... |
arguments to be paseed to methods. |
Value
No return value. Called for its side effects (generates a plot).
Simulated Markov Chain Monte Carlo Sample
Description
a simulated data from the Gibbs sampler.
Usage
data("simMCMC")Format
a numeric vector of length 1000.
Examples
data(simMCMC)