MOCE constructs simultaneous confidence regions after LASSO by debiasing on an expanded model with a ridge-type precision matrix, claiming validity under a=o(n/log p) sparsity.
The first regularity condition on the design matrix X is given as follows
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Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models
MOCE constructs simultaneous confidence regions after LASSO by debiasing on an expanded model with a ridge-type precision matrix, claiming validity under a=o(n/log p) sparsity.