قارن الطرق

	الاستمثال البايزي المتسلسل مع البيانات المفقودة	الاستدلال البايزي مع البيانات المفقودة
المجال	بايزي	بايزي
العائلة	Bayesian methods	Bayesian methods
سنة النشأة	1987	1976–1987
صاحب الطريقة	Tanner & Wong (data augmentation); extended by Gelfand & Smith, Rubin	Rubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation)
النوع	Bayesian computational method	Bayesian probabilistic model
المصدر التأسيسي	Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley. ISBN: 978-0471183860	Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860
الأسماء البديلة	MCMC missing data, data augmentation MCMC, Bayesian multiple imputation, MCMC imputation	Bayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model
ذات صلة	6	6
الملخص	MCMC with missing data is a Bayesian computational strategy that treats unobserved values as additional unknown parameters. By alternating between sampling the missing values from their predictive distribution and sampling the model parameters from their posterior, the algorithm produces a valid joint posterior that fully accounts for uncertainty introduced by the missingness.	Bayesian inference with missing data treats unobserved values as unknown parameters and integrates them out of the posterior distribution. Rather than deleting or ad hoc imputing incomplete records, the method jointly models observed and missing data under an explicit missing-data mechanism, producing fully calibrated posterior uncertainty that honestly reflects what the data cannot tell us.