Package com.esri.arcgis.geoprocessing.tools.spatialstatisticstools

Class Summary
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 Returns the minimum, the maximum, and the average distance to the specified Nth nearest neighbor (N is an input parameter) for a set of features.
CentralFeature Identifies the most centrally located feature in a point, line, or polygon feature class.
ClustersOutliers Given a set of weighted features, identifies statistically significant hot spots, cold spots, and spatial outliers using the Anselin Local Moran's I statistic.
ClustersOutliersRendered Given a set of weighted features, identifies hot spots, cold spots, and spatial outliers using the Anselin Local Moran's I statistic.
CollectEvents Converts event data, such as crime or disease incidents, to weighted point data.
CollectEventsRendered Converts event data to weighted point data and then applies a graduated circle rendering to the resultant count field.
ConvertSpatialWeightsMatrixtoTable Converts a binary spatial weights matrix file (.swm) to a table.
CountRenderer Applies graduated circle rendering to a numeric field in a feature class.
DirectionalDistribution Creates standard deviational ellipses to summarize the spatial characteristics of geographic features: central tendency, dispersion, and directional trends.
DirectionalMean Identifies the mean direction, length, and geographic center for a set of lines.
ExportXYv Exports feature class coordinates and attribute values to a space, comma, or semi-colon delimited ASCII text file.
GenerateNetworkSpatialWeights Constructs a spatial weights matrix file (.swm) using a Network dataset, defining feature spatial relationships in terms of the underlying network structure.
GenerateSpatialWeightsMatrix Constructs a spatial weights matrix (.swm) file to represent the spatial relationships among features in a dataset.
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 using the Getis-Ord General G statistic.
HotSpots The Hot Spot Analysis (Getis-Ord Gi*) tool is contained in the Spatial Statistics Tools tool box.
HotSpotsRendered Calculates the Getis-Ord Gi* statistic for hot spot analysis and then applies a cold-to-hot type of rendering to the output z-scores.
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 features, or the values associated with features, exhibit statistically significant clustering or dispersion over a range of distances.
OrdinaryLeastSquares Performs global Ordinary Least Squares (OLS) linear regression to generate predictions or to model a dependent variable in terms of its relationships to a set of explanatory variables.
SpatialAutocorrelation Measures spatial autocorrelation based on feature locations and attribute values using the Global Moran's I statistic.
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.