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Bejzijevska regresija×Model latentnog rasta krivulje (LGC)×
OblastBajesovska statistikaStatistika
PorodicaBayesian methodsLatent structure
Godina nastanka1990
TvoracMeredith & Tisak
TipBayesian linear modelLatent variable / longitudinal growth model
Temeljni izvorGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗
Drugi nazivibayesian linear regression, probabilistic regression, bayesian regresyonlatent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli
Srodne25
SažetakBayesian 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.
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ScholarGateUporedite metode: Bayesian Regression · LGC Model. Preuzeto 2026-06-19 sa https://scholargate.app/sr/compare