Maximizing Correlation in the Presence of Missing Data

Research output: Contribution to conferencePresentation

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. 
Original languageAmerican English
StatePublished - Nov 2003
EventINFORMS Annual Meeting - Phoenix, AZ
Duration: Oct 14 2012 → …

Conference

ConferenceINFORMS Annual Meeting
Period10/14/12 → …

Keywords

  • Combinatorial optimization
  • Genetic algorithm
  • Integer programming
  • Missing data

DC Disciplines

  • Business

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