|
Activity Number:
|
32
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistics and the Environment
|
| Abstract - #310341 |
|
Title:
|
A Distance-Based Classifier with Application to Microbial Source Tracking
|
|
Author(s):
|
Jayson Wilbur*+
|
|
Companies:
|
Worcester Polytechnic Institute
|
|
Address:
|
Dept of Mathematical Sciences, Worcester, MA, 01609,
|
|
Keywords:
|
|
|
Abstract:
|
Most classification rules can be expressed in terms of distances from the point to be classified to each of the candidate classes. For example, linear discriminant analysis classifies points into the class for which the sample Mahalanobis distance is smallest. However, dependence among these point-to-group distance measures is generally ignored. In this talk, a general classification rule will be defined which uses information about this dependence structure to improve classification. This work was initially motivated by the problem of microbial source tracking which aims to identify sources of fecal contamination in water resources based on genotypic and phenotypic variation in public health indicator organisms such as E. coli. An application of the proposed methodology to microbial source tracking will be presented.
|
- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
Back to the full JSM 2007 program |
