Linganisha mbinu

	Uchanganuzi wa Kutofautisha wa Bayesian	Uchanganuzi wa Kimfumo wa Uhakiki wa Kibayes (BCFA)
Nyanja	Takwimu	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	1964	2007–2012
Mwanzilishi	Seymour Geisser	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov
Aina	Supervised classification / Bayesian inference	Bayesian latent variable model
Chanzo asilia	Geisser, S. (1964). Posterior odds for multivariate normal classifications. Journal of the Royal Statistical Society, Series B, 26(1), 69–76.	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232
Majina mbadala	BDA, Bayesian linear discriminant analysis, Bayesian quadratic discriminant analysis, Bayesian classification	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA
Zinazohusiana	4	4
Muhtasari	Bayesian discriminant analysis assigns observations to predefined groups by combining a multivariate Gaussian likelihood for each class with prior distributions over the class means and covariance matrices. Posterior predictive probabilities replace point-estimate decision boundaries, providing principled uncertainty quantification for classification in small or high-dimensional samples.	Bayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parameter uncertainty naturally.