For continuously observed high-dimensional diffusions with linear drift, the adaptive Lasso is shown to be sign-consistent and asymptotically normal under explicit rate conditions and a sub-Gaussian concentration assumption.
Polynomial rates via deconvolution for nonparametric estimation in McKean-Vlasov SDEs
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Consistent support recovery for high-dimensional diffusions
For continuously observed high-dimensional diffusions with linear drift, the adaptive Lasso is shown to be sign-consistent and asymptotically normal under explicit rate conditions and a sub-Gaussian concentration assumption.