VBel-package {VBel} | R Documentation |
Computes the Gaussian variational approximation of the Bayesian empirical likelihood posterior. This is an implementation of the function found in Yu, W., & Bondell, H. D. (2023) <doi:10.1080/01621459.2023.2169701>.
The DESCRIPTION file:
Package: | VBel |
Type: | Package |
Title: | Variational Bayes for Fast and Accurate Empirical Likelihood Inference |
Version: | 1.0.1 |
Date: | 2024-05-28 |
Authors@R: | c( person("Wei-Chang", "Yu", , "weichang.yu@unimelb.edu.au", role = c("aut"), comment = c(ORCID = "0000-0002-0399-3779")), person("Jeremy", "Lim", , "jeremy.lim@unimelb.edu.au", role = c("cre", "aut")) ) |
Description: | Computes the Gaussian variational approximation of the Bayesian empirical likelihood posterior. This is an implementation of the function found in Yu, W., & Bondell, H. D. (2023) <doi:10.1080/01621459.2023.2169701>. |
License: | GPL (>= 3) |
Imports: | Rcpp (>= 1.0.12), stats |
LinkingTo: | Rcpp, RcppEigen |
Encoding: | UTF-8 |
Roxygen: | list(markdown = TRUE) |
RoxygenNote: | 7.3.1 |
URL: | https://github.com/jlimrasc/VBel |
BugReports: | https://github.com/jlimrasc/VBel/issues |
Suggests: | mvtnorm, testthat (>= 3.0.0) |
Config/testthat/edition: | 3 |
Author: | Wei-Chang Yu [aut] (<https://orcid.org/0000-0002-0399-3779>), Jeremy Lim [cre, aut] |
Maintainer: | Jeremy Lim <jeremy.lim@unimelb.edu.au> |
Archs: | x64 |
Index of help topics:
VBel-package Variational Bayes for Fast and Accurate Empirical Likelihood Inference compute_AEL Compute the Adjusted Empirical Likelihood compute_GVA Compute the Full-Covariance Gaussian VB Empirical Likelihood Posterior diagnostic_plot Check the convergence of a data set computed by 'compute_GVA'
Wei-Chang Yu [aut] (<https://orcid.org/0000-0002-0399-3779>), Jeremy Lim [cre, aut]
Maintainer: Jeremy Lim <jeremy.lim@unimelb.edu.au>
https://www.tandfonline.com/doi/abs/10.1080/01621459.2023.2169701
compute_AEL()
for choice of R and/or C++ computation of AEL
compute_GVA()
for choice of R and/or C++ computation of GVA
diagnostic_plot()
for verifying convergence of computed GVA data
#ansGVARcppPure <- compute_GVA(mu, C_0, h, delthh, delth_logpi, z, lam0, rho,
#elip, a, iters, iters2, fullCpp = TRUE)
#diagnostic_plot(ansGVARcppPure)