# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "VBsparsePCA" in publications use:'
type: software
license: GPL-3.0-only
title: 'VBsparsePCA: The Variational Bayesian Method for Sparse PCA'
version: 0.1.0
doi: 10.32614/CRAN.package.VBsparsePCA
abstract: 'Contains functions for a variational Bayesian method for sparse PCA proposed
  by Ning (2020) <arXiv:2102.00305>. There are two algorithms: the PX-CAVI algorithm
  (if assuming the loadings matrix is jointly row-sparse) and the batch PX-CAVI algorithm
  (if without this assumption). The outputs of the main function, VBsparsePCA(), include
  the mean and covariance of the loadings matrix, the score functions, the variable
  selection results, and the estimated variance of the random noise.'
authors:
- family-names: Ning
  given-names: Bo
  email: bo.ning@upmc.fr
repository: https://yc-ning.r-universe.dev
commit: 019b82aec9554aa00732f9ac20d4395e670d00b5
date-released: '2021-02-13'
contact:
- family-names: Ning
  given-names: Bo
  email: bo.ning@upmc.fr