Partial correlation estimates based on signs

Daniel Vogel, Claudia Köllmann, Roland Fried

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution


We investigate the Oja sign covariance matrix (Oja SCM) for estimating partial correlations in multivariate data. The Oja SCM estimates directly a multiple of the precision matrix and is based on the concept of Oja signs, which generalise the univariate sign function and obey some form of affine equivariance property. We compare it to the classical MLE as well as to estimates based on two alternative multivariate signs: the marginal sign and the spatial sign.
Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Information Theoretic Methods in Science and Engineering
EditorsJ Heikkonen
PublisherTampere International Center for Signal Processing
Number of pages6
Publication statusPublished - 2008


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