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Logistic regression / Sparse PCA / Normal distribution / Multivariate normal distribution / Statistics / Multivariate statistics / Principal component analysis


Sparse logistic principal components analysis for binary data
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Document Date: 2010-03-16 21:45:21

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City

Tokyo / Ibadan / Beijing / /

Company

Pearson / /

Country

Japan / United States / Nigeria / China / /

Facility

Texas A&M University / National Cancer Institute / National Institute of Health / King Abdullah University of Science / Institute of Mathematical Statistics / /

IndustryTerm

grid search / computational algorithm / computation algorithm / iterative weighted least squares algorithm / /

Organization

National Cancer Institute / National Institute of Health / Virtual Center for Collaboration / National Science Foundation / Institute of Mathematical Statistics / King Abdullah University of Science and Technology / Texas A&M University / Harvard School of Public Health / University of Texas / /

Person

See Hunter / Lange / /

Position

CEO / Hunter / probabilistic model for principal components analysis / representative / /

Product

L1 / /

ProvinceOrState

Utah / /

Region

northern Europe / western Europe / /

Technology

single nucleotide polymorphism / Minimization algorithm / computation algorithm / SNP / simulation / computational algorithm / iterative weighted least squares algorithm / using simulation / /

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