Skip to content

00krishna-sandbox/cluster_ident_kulldorff_ant_optimization

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Cluster Identification using Kulldorff Method with Ant Colony Optimization

This project develops some modules to find event clusters in a given dataset. The goal is to determine both the existence and location of event clusters as well as the shape of those clusters.

The challenge of cluster analysis is to first determine whether clustering exists. There are a couple of different approaches to this type of analysis. I use the Kulldorff-Nagarwala method: spatial scan statistic. This approach is good for identifying the location of clusters, however it is not as good at determining the tendency for clustering in a given dataset. Alternative methods of determining clustering tendency are also provided.

The second part of the package provides a method to identify cluster shape. Using some recent work in Ant Colony Optimization methods (Dorigo & Stutzle, 2004) and (Pei, et al., 2013), the package can determine the shape of clusters.

Dependencies

python: numpy 1.8 python: unittest python: rpy2 R: R-3.1.0 R: SpatialEpi-1.1 package

About

Spatial cluster identification modules as well as ant colony optimization to determine the shape of the clusters

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages