We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in a high-dimensional model. It can be easily adjusted for multiplicity taking dependence among tests into account.We analyze its asymptotic properties and establish its asymptotic optimality in terms of semiparametric efficiency.
