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| Bajezijanska prostorna autokorelacija× | Bejzovski kriging (geostatistika zasnovana na modelu)× | |
|---|---|---|
| Oblast | Prostorna analiza | Prostorna analiza |
| Porodica | Regression model | Regression model |
| Godina nastanka≠ | 1991 | 1993–1998 |
| Tvorac≠ | Besag, York & Mollie | Diggle, Tawn & Moyeed; Handcock & Stein |
| Tip≠ | Bayesian hierarchical spatial model | Bayesian spatial interpolation |
| Temeljni izvor≠ | Besag, J., York, J., & Mollie, A. (1991). Bayesian image restoration, with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics, 43(1), 1–20. DOI ↗ | Diggle, P. J., Tawn, J. A., & Moyeed, R. A. (1998). Model-based geostatistics. Journal of the Royal Statistical Society: Series C (Applied Statistics), 47(3), 299–350. DOI ↗ |
| Drugi nazivi | Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSA | Bayesian geostatistics, model-based geostatistics, Bayesian spatial interpolation, stochastic kriging |
| Srodne≠ | 6 | 5 |
| Sažetak≠ | Bayesian Spatial Autocorrelation embeds spatial dependence directly into a Bayesian hierarchical model. A Conditional Autoregressive (CAR) prior encodes the expectation that neighboring areas are more similar than distant ones, and posterior inference is obtained via MCMC. This approach is especially valuable in disease mapping, ecology, and regional science, where small-area estimates need borrowing strength across neighbors. | Bayesian Kriging embeds classical geostatistical interpolation inside a full probabilistic framework. Instead of treating variogram parameters as fixed point estimates, it places prior distributions on them and updates these priors with observed spatial data to obtain a posterior distribution. Predictions at unsampled locations are then marginalised over this uncertainty, yielding honest predictive intervals that account for both spatial dependence and parameter uncertainty. |
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