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Maximizing Correlation in the Presence of Missing Data
INFORMS Annual Meeting (2003)
  • Xinfang Wang, Georgia Southern University
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. 
  • Integer programming,
  • Combinatorial optimization,
  • Genetic algorithm,
  • Missing data
Publication Date
November, 2003
Atlanta, GA
Citation Information
Xinfang Wang. "Maximizing Correlation in the Presence of Missing Data" INFORMS Annual Meeting (2003)
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