Bayesian Latent Class Analysis (BLCA)
Bayesian latent class analysis extends classical LCA by placing prior distributions on all model parameters and using posterior inference — typically via MCMC — to classify individuals into unobserved categorical groups, quantify uncertainty around class membership, and select the number of classes in a principled, probabilistic way.
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Method map
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Izvori
- Dunson, D. B. & Xing, C. (2009). Nonparametric Bayes modeling of multivariate categorical data. Journal of the American Statistical Association, 104(487), 1042–1051. DOI: 10.1198/jasa.2009.tm08439 ↗
- White, A. & Murphy, T. B. (2016). BayesLCA: An R package for Bayesian latent class analysis. Journal of Statistical Software, 61(13), 1–28. DOI: 10.18637/jss.v061.i13 ↗
Kako citirati ovu stranicu
ScholarGate. (2026, June 3). Bayesian Latent Class Analysis. ScholarGate. https://scholargate.app/sr/statistics/bayesian-latent-class-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Bejzijanovska klaster analizaStatistika↔ compare
- Bajezijanska konfirmatorna faktorska analiza (BCFA)Psihometrija↔ compare
- Bajezijansko modelovanje smešaStatistika↔ compare
- Latent Class Analysis (LCA)Statistika↔ compare
- Analiza latentnih profila (LPA)Psihometrija↔ compare
- Моделирање мешавинаStatistika↔ compare
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