Abstract Details
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Activity Number:
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190
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #308028 |
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Title:
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Optimization of PRIM Under Normality
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Author(s):
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Daniel A. Diaz*+ and J. Sunil Rao and Jean-Eudes Dazard
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Companies:
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Biostatistics Unit - University of Miami and University of Miami and Center for Proteomics and Bioinformatics - Case Western Reserve University
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Keywords:
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PRIM ;
Bump hunting ;
Principal Components Analysis ;
Normality ;
High dimensionality
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Abstract:
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We modify the PRIM algorithm to obtain a converging region under normality reducing the whole complexity of the algorithm to a single step. This reduction is shown to be useful in practice via the central limit theorem. We prove several interesting results comparing forms of PRIM, including that the final box resulting from PRIM is more accurate on the rotation induced by the principal components.
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Authors who are presenting talks have a * after their name.
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