পদ্ধতির তুলনা করুন

	অনুপস্থিত তথ্য সহ এমসিএমসি	অজানা ডেটা সহ বায়েসিয়ান অনুমান (Bayesian Inference with Missing Data)
ক্ষেত্র	বেইসীয়	বেইসীয়
পরিবার	Bayesian methods	Bayesian methods
উদ্ভবের বছর	1987	1976–1987
প্রবর্তক	Tanner & Wong (data augmentation); extended by Gelfand & Smith, Rubin	Rubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation)
ধরন	Bayesian computational method	Bayesian probabilistic model
মৌলিক উৎস	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
অপর নাম	MCMC missing data, data augmentation MCMC, Bayesian multiple imputation, MCMC imputation	Bayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model
সম্পর্কিত	6	6
সারসংক্ষেপ	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.