The debiased Lasso adds an approximate inverse-Gram correction to a Lasso estimate so that each corrected coordinate has an asymptotically linear expansion.
The nodewise Lasso regresses each design column on the remaining columns and uses its residual to estimate a column of the inverse covariance or inverse Gram matrix.
Under sparsity, compatibility, and inverse-Gram estimation conditions, the standardized coordinatewise error of the Debiased Lasso converges in distribution to a standard normal distribution.
Articles by others on the same topic
There are currently no matching articles.