विधियों की तुलना करें

	बेयसियन रिग्रेशन	प्रच्छन्न वृद्धि वक्र मॉडल (LGC)
क्षेत्र	बायेसियन	सांख्यिकी
परिवार	Bayesian methods	Latent structure
उद्भव वर्ष	—	1990
प्रवर्तक	—	Meredith & Tisak
प्रकार	Bayesian linear model	Latent variable / longitudinal growth model
मौलिक स्रोत	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122.
उपनाम	bayesian linear regression, probabilistic regression, bayesian regresyon	latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli
संबंधित	2	5
सारांश	Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.	The latent growth curve model is a structural equation modelling approach introduced by Meredith and Tisak (1990) for analysing change over time. It treats each individual's starting point (intercept) and rate of change (slope) as latent variables, simultaneously estimating the average trajectory across the sample and the extent to which individuals differ in their own trajectories.