The Utilities toolset contains tools that perform a variety of data conversion tasks. These tools can be used in conjunction with other tools in the Spatial Statistics toolbox.
| Tool | Description |
|---|---|
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. Results are written as tool execution messages. | |
Calculates crude or smoothed rates. The global empirical Bayes rate method smooths the rates toward a global reference rate. The local empirical Bayes, locally weighted average, and locally weighted median rate methods use local neighbors to spatially smooth rates. | |
Converts event data, such as crime or disease incidents, to weighted point data. | |
Prepares interactive pop-up charts for web display by saving them as image attachments to a feature class. | |
Converts a binary spatial weights matrix file (.swm) to a table. | |
Describes the contents and diagnostics of a spatial statistics model file. | |
Reduces the number of dimensions of a set of continuous variables by aggregating the highest possible amount of variance into fewer components using Principal Component Analysis (PCA) or Reduced-Rank Linear Discriminant Analysis (LDA). | |
Exports feature class coordinates and attribute values to a space-, comma-, tab-, or semicolon-delimited ASCII text file. | |
Adds descriptions and units to the variables stored in a spatial statistics model file. | |
Smooths a numeric variable of one or more time series using centered, forward, and backward moving averages, as well as an adaptive method based on local linear regression. After smoothing short-term fluctuations, longer-term trends or cycles often become apparent. |