ScholarGate
Asistent

Usporedite metode

Pregledajte odabrane metode jednu uz drugu; retci koji se razlikuju su istaknuti.

Bayesijeva mreža s pogreškom mjerenja×Bayesovo zaključivanje s pogreškom mjerenja×
PodručjeBayesovska statistikaBayesovska statistika
ObiteljBayesian methodsBayesian methods
Godina nastanka1988 (Bayesian networks); measurement-error extension: 1990s1993
TvoracJudea Pearl (Bayesian networks); measurement-error extension developed in epidemiology and psychometrics through the 1990s–2000sRichardson & Gilks (Bayesian formulation); Carroll et al. (comprehensive framework)
VrstaProbabilistic graphical model with latent variablesBayesian errors-in-variables model
Temeljni izvorPearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann. ISBN: 978-1558604797Carroll, R. J., Ruppert, D., Stefanski, L. A., & Crainiceanu, C. M. (2006). Measurement Error in Nonlinear Models: A Modern Perspective (2nd ed.). Chapman & Hall/CRC. ISBN: 978-1584886433
Drugi naziviBN-ME, errors-in-variables Bayesian network, Bayesian graphical model with measurement error, latent variable Bayesian networkBayesian errors-in-variables model, Bayesian EIV model, Bayesian measurement error model, Bayesian misclassification model
Srodne55
SažetakA Bayesian network with measurement error is a probabilistic directed acyclic graphical model in which one or more node variables are observed with error rather than exactly. Latent true-value nodes are introduced for mismeasured variables, and the model jointly infers the network's conditional probability parameters and the unobserved true values from the noisy observations.Bayesian inference with measurement error extends the standard Bayesian framework to situations where one or more covariates or outcomes are observed with noise or misclassification. By treating the true unobserved values as latent variables and assigning them priors, the model jointly estimates the true exposure distribution and the structural parameters of interest, propagating all uncertainty through the posterior.
ScholarGateSkup podataka
  1. v1
  2. 2 Izvori
  3. PUBLISHED
  1. v1
  2. 2 Izvori
  3. PUBLISHED

Idi na pretraživanje Preuzmi prezentaciju

ScholarGateUsporedite metode: Bayesian Network with Measurement Error · Bayesian Inference with Measurement Error. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare