Salīdzināt metodes

	Bayesian Spatial Autocorrelation	Lokālā telpiskā autokorelācija
Nozare	Telpiskā analīze	Telpiskā analīze
Saime	Regression model	Regression model
Izcelsmes gads	1991	1995
Autors	Besag, York & Mollie	Luc Anselin
Tips	Bayesian hierarchical spatial model	Spatial association analysis
Pirmavots	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.	Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115.
Citi nosaukumi	Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSA	local spatial association, local SA, LISA methods, local spatial clustering
Saistītās	6	6
Kopsavilkums	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.	Local Spatial Autocorrelation methods decompose global spatial clustering into location-specific statistics, revealing where in a study area significant clustering or dispersion occurs. Each observation receives its own association score and significance value, enabling the detection of spatial hot spots, cold spots, and spatial outliers rather than reporting a single summary statistic.