Maximizing Correlation in the Presence of Missing Data

Authors

Xinfang Wang, Georgia Southern UniversityFollow

Document Type

Article

Publication Date

2008

Publication Title

Applied Mathematical Sciences

ISSN

1314-7552

Abstract

In this paper we address the problem of maximizing the correlation between two vectors of time series data, when one of the vectors has missing data and the timing of the missing data is unknown. The motivation for this work comes from environmental monitoring where because of monitoring malfunction, some data are lost. We study the use of integer programming and a genetic algorithm (GA) for this problem.

Recommended Citation

Wang, Xinfang. 2008. "Maximizing Correlation in the Presence of Missing Data." Applied Mathematical Sciences, 2 (54): 2653-2664.
https://digitalcommons.georgiasouthern.edu/logistics-supply-facpubs/43