Maximizing Correlation in the Presence of Missing Data

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

MoreLess

Year of publication:	2007
Authors:	Camm, Jeffrey ; Wang, Xinfang (Jocelyn)
Publisher:	[S.l.] : SSRN
Subject:	Korrelation \| Correlation \| Theorie \| Theory \| Fehlende Daten \| Missing data \| Datenqualität \| Data quality

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Extent:	1 Online-Ressource (15 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 2007 erstellt
Other identifiers:	10.2139/ssrn.934016 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014055540