Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Simulim Bootstrap Multilevel× | Kampimi i Gibbs× | |
|---|---|---|
| Fusha | Statistika bajesiane | Statistika bajesiane |
| Familja | Bayesian methods | Bayesian methods |
| Viti i origjinës≠ | 1979 (bootstrap); multilevel variants c.1990s | 1984 |
| Krijuesi≠ | Efron (1979); multilevel extensions developed through 1980s–2000s | Stuart Geman & Donald Geman |
| Lloji≠ | resampling / simulation | MCMC sampling algorithm |
| Burimi themelues≠ | Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1–26. DOI ↗ | Geman, S. & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721-741. DOI ↗ |
| Emërtime të tjera | hierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resampling | Gibbs sampler, coordinate-wise MCMC, systematic scan Gibbs, blocked Gibbs sampling |
| Të lidhura≠ | 6 | 5 |
| Përmbledhja≠ | Multilevel bootstrap simulation is a resampling technique designed for clustered or hierarchically structured data. It preserves the nested data structure by resampling at each level independently — first drawing clusters (e.g., schools, hospitals), then drawing observations within each sampled cluster — so that bootstrap replicate datasets reflect the same multilevel organisation as the original data. | Gibbs sampling is a Markov chain Monte Carlo algorithm that approximates a high-dimensional posterior distribution by repeatedly drawing each parameter from its full conditional distribution given all other parameters and the data. Because each draw is exact from a conditional — not a proposal that may be rejected — the sampler is efficient when those conditionals are available in closed form. |
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