Spatial Regression
Spatial regression is a statistical method used to analyze the relationship between a dependent variable and one or more independent variables, taking into account the spatial autocorrelation of the data. It is commonly used in fields such as geography, ecology, and epidemiology to model spatial patterns and relationships. Spatial regression models can account for the fact that observations that are close together in space are likely to be more similar than observations that are far apart. This method can help to identify spatial patterns and relationships that may not be apparent using traditional regression methods. Spatial regression can be used for both continuous and categorical data, and can incorporate spatially varying coefficients and non-linear relationships.
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