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Bootstrap simulacija s nedostajućim podacima×Bayesijanska inferencija s nedostajućim podacima×
PodručjeBayesovska statistikaBayesovska statistika
ObiteljBayesian methodsBayesian methods
Godina nastanka1979–1990s1976–1987
TvoracBradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and othersRubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation)
VrstaResampling simulationBayesian probabilistic model
Temeljni izvorEfron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC. ISBN: 978-0412042317Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860
Drugi nazivibootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MIBayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model
Srodne56
SažetakBootstrap simulation with missing data combines resampling-based variance estimation with principled handling of incomplete observations. Rather than deleting cases or assuming complete data, the method integrates imputation or weighting directly into the bootstrap loop, propagating the additional uncertainty due to missingness into the final standard errors and confidence intervals.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.
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  3. PUBLISHED

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ScholarGateUsporedite metode: Bootstrap Simulation with Missing Data · Bayesian Inference with Missing Data. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare