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| Suy luận Bayes với dữ liệu thiếu× | Tính toán Bayes xấp xỉ với dữ liệu thiếu× | |
|---|---|---|
| Lĩnh vực | Bayes | Bayes |
| Họ | Bayesian methods | Bayesian methods |
| Năm ra đời≠ | 1976–1987 | 2002 (ABC); 1987 (missing data theory) |
| Người khởi xướng≠ | Rubin, D. B. (missing-data mechanisms); Tanner & Wong (data augmentation) | Beaumont, Zhang & Balding (ABC); Rubin (missing data framework) |
| Loại≠ | Bayesian probabilistic model | likelihood-free Bayesian inference |
| Công trình gốc≠ | Little, R. J. A. & Rubin, D. B. (2002). Statistical Analysis with Missing Data (2nd ed.). Wiley-Interscience. ISBN: 978-0471183860 | Beaumont, M. A., Zhang, W. & Balding, D. J. (2002). Approximate Bayesian computation in population genetics. Genetics, 162(4), 2025–2035. link ↗ |
| Tên gọi khác | Bayesian missing data analysis, Bayesian data augmentation, Bayesian imputation, missing data Bayesian model | ABC with missing data, likelihood-free inference with missing data, simulation-based inference for incomplete data, ABC-MD |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | 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. | Approximate Bayesian Computation with missing data extends the likelihood-free ABC framework to settings where observations are incomplete or partially recorded. By simulating data under a posited model and accepting parameter draws whose simulated summary statistics are close to the observed ones, it bypasses the need to evaluate an intractable likelihood — even when some data values are absent. |
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