LASSO-Patternsearch Algorithm with Application to Ophthalmology and Genomic Data

LASSO-Patternsearch Algorithm with Application to Ophthalmology and Genomic Data (2008)

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by Weiliang Shi , Grace Wahba , Stephen Wright , Kristine Lee , Ronald Klein , Barbara Klein

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@MISC{Shi08lasso-patternsearchalgorithm,
    author = {Weiliang Shi and Grace Wahba and Stephen Wright and Kristine Lee and Ronald Klein and Barbara Klein},
    title = { LASSO-Patternsearch Algorithm with Application to Ophthalmology and Genomic Data},
    year = {2008}
}

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Abstract

The LASSO-Patternsearch algorithm is proposed to efficiently identify patterns of multiple dichotomous risk factors for outcomes of interest in demographic and genomic studies. The patterns considered are those that arise naturally from the log linear expansion of the multivariate Bernoulli density. The method is designed for the case where there is a possibly very large number of candidate patterns but it is believed that only a relatively small number are important. A LASSO is used to greatly reduce the number of candidate patterns, using a novel computational algorithm that can handle an extremely large number of unknowns simultaneously. The patterns surviving the LASSO are further pruned in the framework of (parametric) generalized linear models. A novel tuning procedure based on the GACV for Bernoulli outcomes, modified to act

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