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Reduced rank stochastic regression with a sparse singular value decomposition

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Reduced rank stochastic regression with a sparse singular value decomposition (English)

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Kun Chen

1

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Nils Christian Stenseth

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Nils Chr. Stenseth

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3

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Kung-Sik Chan

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2

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publication date

3 November 2011

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published in

Journal of the Royal Statistical Society Series B: Statistical Methodology

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volume

74

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issue

2

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page(s)

203-221

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Penalized methods for bi-level variable selection

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Least angle regression

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Biclustering via sparse singular value decomposition

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Capturing heterogeneity in gene expression studies by surrogate variable analysis

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Statistical Significance of Clustering for High-Dimension, Low–Sample Size Data

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Regularized Multivariate Regression for Identifying Master Predictors with Application to Integrative Genomics Study of Breast Cancer

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Ecological and genetic impact of Atlantic cod larval drift in the Skagerrak.

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Discovering genetic associations with high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach

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A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis

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Identifiers

DOI

10.1111/J.1467-9868.2011.01002.X

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zbMATH Open document ID

1411.62182

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(Q57039786)

Reduced rank stochastic regression with a sparse singular value decomposition

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