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Gibbs Sampling with Measurement Error/Evidence
Method evidence record

Gibbs Sampling with Measurement Error

Gibbs sampling with measurement error is a Bayesian MCMC method that jointly estimates unknown true covariate values and model parameters when the observed data are corrupted by measurement error. By treating the latent true values as additional unknowns, it samples all quantities iteratively from their full conditional distributions, propagating measurement uncertainty into every downstream inference.

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Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Gibbs Sampling for Models with Measurement Error
Taxonomic method record · bayesian / bayesian
  • Gelfand, A. E. & Smith, A. F. M. (1990). Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85(410), 398–409. · DOI 10.1080/01621459.1990.10476213
  • Richardson, S. & Gilks, W. R. (1993). A Bayesian approach to measurement error problems in epidemiology using conditional independence models. American Journal of Epidemiology, 138(6), 430–442. · DOI 10.1093/oxfordjournals.aje.a116875
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketBayesian Inference with Measurement Errormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGibbs Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketHamiltonian Monte Carlo with Measurement Errormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMCMC with Measurement Errormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMetropolis-Hastings with measurement errormachine-suggested · Relational suggestion, not evidence.

Evidence status

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Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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