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High Dimensional Influence Measure
Cook’s distance High dimensional diagnosis Influential obser- vation Lasso Marginal correlations Variable Screening
2016/1/20
Influence diagnosis is important since presence of influential ob-servations could lead to distorted analysis and misleading interpreta-tions. For high dimensional data, it is particularly so, as the ...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
Tight conditions for consistent variable selection high dimensional nonparametric regression
2011/3/23
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the num...
Compressible Priors for High-dimensional Statistics
linear inverse problem LASSO sparsity sparse regression ridge regression com-pressible prior compressive sensing instance optimality maximum a posteriori high-dimensional statistics order statistics
2011/3/18
We develop a principled way of identifying probability distributions whose independent and identically distributed (iid) realizations are compressible, i.e., can be approximated as sparse. We focus on...