JSM 2005 - Toronto

Abstract #302825

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Activity Number: 472
Type: Invited
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Physical and Engineering Sciences
Abstract - #302825
Title: Multiblock Relationships in High Dimensions
Author(s): Douglas M. Hawkins*+ and Despina Stefan
Companies: University of Minnesota and University of Minnesota
Address: School of Statistics, Minneapolis, MN, 55455-0493,
Keywords:
Abstract:

The familiar canonical correlation formulation deals with the relationship between two vector-valued random variables and has been extended to settings with three or more vector-valued variables. This setting is increasingly interesting in a number of settings. For example, the members of a pharmaceutical chemical library may be described by a vector of observed clinical effects, a vector of Aspergillus mutagenicity measures, and a vector of molecular descriptors. This leads to the problem of finding linear (or nonlinear) functions of the separate vectors that show the commonality between the three types of measures. Such datasets typically are of very high dimension, however, and multiblock methods motivated by social science problems are unsatisfactory to address problems such as apparent rank near-deficiencies, which arise in high dimension, without adaptation. We present some adaptations of this sort and address the related problem of model diagnostics.

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