A1 Refereed original research article in a scientific journal
Multivariate L-1 Methods: The Package MNM
Authors: Nordhausen K, Oja H
Publisher: JOURNAL STATISTICAL SOFTWARE
Publication year: 2011
Journal: Journal of Statistical Software
Journal name in source: JOURNAL OF STATISTICAL SOFTWARE
Journal acronym: J STAT SOFTW
Volume: 43
Issue: 5
First page : 1
Last page: 28
Number of pages: 28
ISSN: 1548-7660
Abstract
In the paper we present an R package MNM dedicated to multivariate data analysis based on the L-1 norm. The analysis proceeds very much as does a traditional multivariate analysis. The regular L-2 norm is just replaced by different L-1 norms, observation vectors are replaced by their (standardized and centered) spatial signs, spatial ranks, and spatial signed-ranks, and so on. The procedures are fairly efficient and robust, and no moment assumptions are needed for asymptotic approximations. The background theory is briefly explained in the multivariate linear regression model case, and the use of the package is illustrated with several examples using the R package MNM.
In the paper we present an R package MNM dedicated to multivariate data analysis based on the L-1 norm. The analysis proceeds very much as does a traditional multivariate analysis. The regular L-2 norm is just replaced by different L-1 norms, observation vectors are replaced by their (standardized and centered) spatial signs, spatial ranks, and spatial signed-ranks, and so on. The procedures are fairly efficient and robust, and no moment assumptions are needed for asymptotic approximations. The background theory is briefly explained in the multivariate linear regression model case, and the use of the package is illustrated with several examples using the R package MNM.
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