Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uigaji wa uhimilivu kwa data yenye upungufu× | Utaftaji wa Bayesian wenye Data Zilizokosekana× | |
|---|---|---|
| Nyanja | Mbinu za Bayes | Mbinu za Bayes |
| Familia | Bayesian methods | Bayesian methods |
| Mwaka wa asili≠ | 1979–1990s | 1976–1987 |
| Mwanzilishi≠ | Bradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and others | Rubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation) |
| Aina≠ | Resampling simulation | Bayesian probabilistic model |
| Chanzo asilia≠ | Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC. ISBN: 978-0412042317 | Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860 |
| Majina mbadala | bootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MI | Bayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | Bootstrap 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. |
| ScholarGateSeti ya data ↗ |
|
|