Módszerek összehasonlítása

	Bayesian Hot Spot Analysis	Bayesian Spatial Autocorrelation
Tudományterület	Térbeli elemzés	Térbeli elemzés
Módszercsalád	Regression model	Regression model
Keletkezés éve	1987	1991
Megalkotó	Clayton & Kaldor (1987); Lawson (2001 onward)	Besag, York & Mollie
Típus	Bayesian spatial cluster detection	Bayesian hierarchical spatial model
Alapmű	Lawson, A. B. (2018). Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology (3rd ed.). CRC Press. ISBN: 978-1138575424	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.
Alternatív nevek	Bayesian spatial cluster detection, Bayesian disease mapping hot spots, empirical Bayesian hot spot analysis, Bayesian spatial smoothing hot spots	Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSA
Kapcsolódó	5	6
Összefoglaló	Bayesian Hot Spot Analysis identifies spatial clusters of elevated risk or intensity by combining observed data with prior beliefs about spatial structure. It uses Bayesian smoothing — pooling information across neighboring areas — to stabilize estimates in small areas and then flags locations where the posterior probability of exceeding a risk threshold is high.	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.