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Quantile Regression for Analyzing Heterogeneity in Ultra-high Dimension
Ultra-high dimensional data often display heterogeneity due to either heteroscedastic variance or other forms of non-location-scale covariate effects. To accommodate heterogeneity, we advocate a more general interpretation of sparsity which assumes that only a small number of covariates influence th...
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| Main Authors: | , , |
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| פורמט: | Artigo |
| שפה: | Inglês |
| יצא לאור: |
2012
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| נושאים: | |
| גישה מקוונת: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3471246/ https://ncbi.nlm.nih.gov/pubmed/23082036 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/01621459.2012.656014 |
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