NDLI: A Remark on the Use of a Weight Matrix in the Linear Model of Coregionalization

Content Provider	Springer Nature Link
Author	Oman, Samuel D. Vakulenko Lagun, Bella
Copyright Year	2011
Abstract	The linear model of coregionalization (LMC) is generally fit to multivariate geostatistical data by minimizing a least-squares criterion. It is commonly believed that weighting the criterion by inverse variances will reduce the influence of those variables with large variance. We point out that this need not be so, and that in some cases the weights will have no effect whatsoever on the estimated sill matrices. When there is an effect, it is due not to a reduction of these variables’ influence, but rather due to a lack of invariance of the minimization problem; moreover, sometimes the influence may actually increase. The correct way to reduce influence is to fit the LMC after standardizing the variables to have unit variance.
Starting Page	505
Ending Page	512
Page Count	8
File Format	PDF
ISSN	18748961
Journal	Mathematical Geosciences
Volume Number	44
Issue Number	4
e-ISSN	18748953
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-10-21
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Factor analysis Invariance Linear model of coregionalization Principal components Standardization Earth Sciences Geotechnical Engineering & Applied Earth Sciences Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Hydrogeology
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Mathematics

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A Remark on the Use of a Weight Matrix in the Linear Model of Coregionalization