Relating multivariate time-series by linear three-way decomposition (LTD) and partial least squares (PLS) analysis.
The problem of relating multivariate time-series which is common in drug development is considered. The mathematical and statistical problems involve relating two three-way tables. These tables have objects and time-points in common while the variables to be related are unique for each table. A modification is presented of the linear three-way decomposition (LTD) algorithm which directly incorporates the information that both objects and time-points are common to the two tables. A comparison is made with partial least squares (PLS) analysis both at the theoretical level and in their application to three sets of real data. Limitations of LTD are discussed, in particular the constraint imposed by the trilinearity requirement, and areas for future development are proposed.
Ståhle
L
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Department of Pharmacology, Karolinska Institute, Stockholm, Sweden.
D000661:Amphetamine / Q000494:pharmacology; D000818:Animals; D001777:Blood Coagulation / Q000187:drug effects; D006801:Humans; D016018:Least-Squares Analysis; D016014:Linear Models; D008432:Mathematical Computing; D008781:Methyltyrosines / Q000494:pharmacology; D008954:Models, Biological; D015999:Multivariate Analysis; D051381:Rats; D019805:alpha-Methyltyrosine
D008781:Methyltyrosines; D019805:alpha-Methyltyrosine; D000661:Amphetamine