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VARIABLE SELECTION AND PREDICTION WITH INCOMPLETE HIGH-DIMENSIONAL DATA()
We propose a Multiple Imputation Random Lasso (mirl) method to select important variables and to predict the outcome for an epidemiological study of Eating and Activity in Teens. In this study 80% of individuals have at least one variable missing. Therefore, using variable selection methods develope...
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| I publikationen: | Ann Appl Stat |
|---|---|
| Huvudupphovsmän: | , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2016
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4872715/ https://ncbi.nlm.nih.gov/pubmed/27213023 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/15-AOAS899 |
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