# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "vbpm" in publications use:' type: software license: GPL-3.0-only title: 'vbpm: Variational Bayes Psychometric Models' version: 0.9.1 identifiers: - type: doi value: 10.32614/CRAN.package.vbpm abstract: Variational Bayes estimation for a family of psychometric measurement models. Two models are provided. Variational Bayes factor analysis (vbfa) is a regularized partially confirmatory factor model spanning the confirmatory-exploratory continuum via spike-and-slab priors on the loadings (Chen, Guo, Zhang, and Pan, 2021 ; Chen, 2023 ; Jin and Chen, 2025 ), with an optional dynamic (warm-started) regularization path, an orthogonal bifactor parameterization, and optional sparse residual (local dependence) estimation through a graphical spike-and-slab prior solved by QUIC (Jin, Chen, Yan, and Zhang, 2026 ). Regularized MIMIC (vbmimic) extends this to multiple-indicators multiple-causes models, placing spike-and-slab priors on both the measurement and the structural part (Jin and Chen, 2025 ). Companion tools compute SEM-like fit statistics, and sweep a factor-count window to report candidate fit, criterion, and between-candidate loading-correspondence measurements without selecting a count (Chen and Jin, 2026 ). Data generators for either model family are also provided. authors: - family-names: Chen given-names: Jinsong email: jinsong.chen@live.com orcid: https://orcid.org/0000-0002-0157-5469 - family-names: Jin given-names: Yi orcid: https://orcid.org/0000-0002-8604-5992 preferred-citation: type: manual title: 'vbpm: Variational Bayes Psychometric Models' authors: - family-names: Chen given-names: Jinsong email: jinsong.chen@live.com orcid: https://orcid.org/0000-0002-0157-5469 - family-names: Jin given-names: Yi orcid: https://orcid.org/0000-0002-8604-5992 year: '2026' notes: R package version 0.9.1 url: https://github.com/Jinsong-Chen/vbpm repository: https://jinsong-chen.r-universe.dev repository-code: https://github.com/Jinsong-Chen/vbpm commit: ac7747a47e98f20091ab319347c1ade16a6b1e77 url: https://github.com/Jinsong-Chen/vbpm date-released: '2026-08-24' contact: - family-names: Chen given-names: Jinsong email: jinsong.chen@live.com orcid: https://orcid.org/0000-0002-0157-5469 references: - type: article title: Regularized variational approximation for partially confirmatory factor analysis authors: - family-names: Jin given-names: Yi - family-names: Chen given-names: Jinsong journal: 'Structural Equation Modeling: A Multidisciplinary Journal' year: '2025' volume: '32' issue: '3' doi: 10.1080/10705511.2024.2432612 start: '437' end: '449' - type: article title: Sparse residual estimation in partially confirmatory factor analysis authors: - family-names: Jin given-names: Yi - family-names: Chen given-names: Jinsong - family-names: Yan given-names: Zi - family-names: Zhang given-names: Ying journal: PsyArXiv preprint year: '2026' doi: 10.31234/osf.io/dehtv_v2 - type: article title: Regularized variational Bayesian approximations for variable selection in extended multiple-indicators multiple-causes models authors: - family-names: Jin given-names: Yi - family-names: Chen given-names: Jinsong journal: Multivariate Behavioral Research year: '2025' doi: 10.1080/00273171.2025.2483253 - type: article title: 'Recovering latent structures after variational Bayesian variable selection: Fit assessment and factor-number selection in partially exploratory factor analysis' authors: - family-names: Chen given-names: Jinsong - family-names: Jin given-names: Yi journal: arXiv preprint year: '2026' notes: arXiv:2607.07159 url: https://arxiv.org/abs/2607.07159