# The SPATIALREG Procedure

The SPATIALREG procedure analyzes spatial econometric models for cross-sectional data in which observations in the data are spatially referenced or georeferenced. For example, housing price data that
are collected from 48 continental states in the United States fall into the category of spatially referenced data. Compared to nonspatial regression models, spatial econometric models are capable
of handling spatial interaction and spatial heterogeneity in a regression setting.

The SPATIALREG procedure estimates the parameters of a regression model by maximum likelihood techniques and supports the following models:

- linear model
- linear model with spatial lag of X (SLX) effects
- spatial autoregressive (SAR) model
- spatial Durbin model (SDM)
- spatial error model (SEM)
- spatial Durbin error model (SDEM)
- spatial moving average (SMA) model
- spatial Durbin moving average (SDMA) model
- spatial autoregressive moving average (SARMA) model
- spatial Durbin autoregressive moving average (SDARMA) model
- spatial autoregressive confused (SAC) model
- spatial Durbin autoregressive confused (SDAC) model

## Documentation

For further details, see the *SAS/ETS*^{®} User's Guide

## Examples