Linganisha mbinu

	Bayesian Moran's I	Uhuru wa Angani wa Kibayesiyani (Bayesian Spatial Autocorrelation)
Nyanja	Uchanganuzi wa Kimaeneo	Uchanganuzi wa Kimaeneo
Familia	Regression model	Regression model
Mwaka wa asili	1950 / 2000s	1991
Mwanzilishi	Moran (1950), Bayesian extension developed in spatial statistics literature (late 1990s–2000s)	Besag, York & Mollie
Aina	Bayesian spatial autocorrelation test	Bayesian hierarchical spatial model
Chanzo asilia	Haining, R. (2003). Spatial Data Analysis: Theory and Practice. Cambridge University Press. ISBN: 9780521774611	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.
Majina mbadala	Bayesian spatial autocorrelation test, Bayesian Moran statistic, Moran's I under Bayesian inference, Bayesian global spatial association	Bayesian spatial dependence, Bayesian LISA, Bayesian spatial clustering, BSA
Zinazohusiana	6	6
Muhtasari	Bayesian Moran's I embeds the classical Moran's I spatial autocorrelation test within a Bayesian probabilistic framework. Rather than producing a single p-value, it yields a posterior distribution over the spatial autocorrelation parameter, enabling uncertainty quantification, incorporation of prior knowledge, and more principled inference in small or irregular spatial datasets.	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.