Spatial regression models are statistical tools used to analyze spatial data, accounting for the relationships between variables that are influenced by geographical locations. These models help understand how spatially correlated data can affect the relationships among variables, allowing for more accurate predictions and insights in various fields such as urban planning, environmental studies, and social sciences.
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