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Published in 2020 at "Statistica Sinica"
DOI: 10.5705/ss.202018.0008
Abstract: Block-wise missing data are becoming increasingly common in highdimensional biomedical, social, psychological, and environmental studies. As a result, we need efficient dimension-reduction methods for extracting important information for predictions under such data. Existing dimension-reduction methods…
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Keywords:
wise missing;
missing data;
factor regression;
factor ... See more keywords