| | Class | Description |
|---|
 | AverageNearestNeighbor | Calculates a nearest neighbor index based on the average distance from each feature to its nearest neighboring feature. |
| CalculateAreas | Calculates Area values for each feature in a polygon feature class. |
| CalculateDistanceBand | Calculates the distance for all features in the input feature class to their nth neighbor. |
| CentralFeature | Identifies the most centrally located feature in a point, line, or polygon feature class. |
| ClustersOutliers | Given a set of weighted data points, identifies spatial clusters of extreme values and spatial outliers. |
| ClustersOutliersRendered | Identifies and renders spatial clusters of extreme values and spatial outliers. |
| CollectEvents | Converts event data, such as crimes or disease incidents, to weighted point data. |
| CollectEventsRendered | Converts event data to weighted point data and applies a graduated circle rendering to the count field. |
| ConvertSpatialWeightsMatrixtoTable | Converts a Spatial Weights Matrix (*.swm) to a database table. |
| CountRenderer | Applies graduated circle rendering to a numeric field in a feature class. |
| DirectionalDistribution | Measures whether a distribution of features exhibits a directional trend. |
| DirectionalMean | Identifies the general (mean) direction for a set of lines. |
| ExportXYv | Exports feature class coordinates and attribute values to a space-, comma-, or semicolon-delimited ASCII text file. |
| GenerateNetworkSpatialWeights | Creates a spatial weights matrix file based on the locations in an input feature class in relation to a network dataset. |
| GenerateSpatialWeightsMatrix | Creates a spatial weights matrix (*.swm) file from an input feature class. |
| GeographicallyWeightedRegression | Performs Geographically Weighted Regression (GWR), a local form of linear regression used to model spatially varying relationships. |
| HighLowClustering | Measures the degree of clustering for either high values or low values. |
| HotSpots | Calculates the Getis-Ord Gi* statistic to identify spatial clusters of high and low values. |
| HotSpotsRendered | Identifies and renders spatial clusters of high and low values. |
| MeanCenter | Identifies the geographic center (or the center of concentration) for a set of features. |
| MedianCenter | Identifies the location that minimizes overall Euclidean distance to the features in a dataset. |
| MultiDistanceSpatialClustering | Determines whether a feature class is clustered at multiple different distances. |
| OrdinaryLeastSquares | Computes a linear regression model using Ordinary Least Squares. |
| SpatialAutocorrelation | Measures spatial autocorrelation based on feature locations and attribute values. |
| StandardDistance | Measures the degree to which features are concentrated or dispersed around the geometric mean center. |
| ZRenderer | Applies a cold (blue) to hot (red) color rendering scheme for a field of z-scores. |
