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SPARSE LOGISTIC PRINCIPAL COMPONENTS ANALYSIS FOR BINARY DATA
We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of the success probabilities of the binary observations. Sparsity is introdu...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2010
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC2992445/ https://ncbi.nlm.nih.gov/pubmed/21116451 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/10-AOAS327SUPP |
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