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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "scmix" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'scmix: Bayesian Model-Based Clustering with Sparse Conditional Mixture Models'
version: 0.1.1
doi: 10.32614/CRAN.package.scmix
abstract: 'Fits Bayesian sparse conditional (Gaussian) mixture models for model-based
  clustering. Each mixture component factorizes into a chain of univariate polynomial
  regressions with per-component, per-equation Bayesian variable selection under a
  centered Zellner g-prior; the number of clusters is selected within a single run
  via an overfitted sparse mixture (Dirichlet concentration 1/K). The blocked Gibbs
  sampler draws the selection sets exactly by enumeration (or by validated single-flip
  Metropolis-Hastings in higher dimension), is provably well-posed under a documented
  proper fallback prior, and reports a label-invariant consensus partition (Dahl''s
  least-squares criterion). Companion package to Dong, Liao, and Lee (2026), "Replacing
  three nested searches with one sweep: a Bayesian treatment of sparse conditional
  mixture clustering". Multiple-imputation functionality for the same engine is also
  exposed.'
authors:
- family-names: Dong
  given-names: Aqi
  email: donga2@erau.edu
- family-names: Liao
  given-names: Yang-Li
  email: yanglliao@fcu.edu.tw
- family-names: Lee
  given-names: Danhyang
  email: danhyang@smu.edu
repository: https://cran.r-universe.dev
commit: 858fafb7ff6062c0d1bd7f313078828f54a2996c
date-released: '2026-08-20'
contact:
- family-names: Dong
  given-names: Aqi
  email: donga2@erau.edu