In an empirical Bayes analysis, we use data from repeated sampling to imitate inferences made by oracle Bayesian with extensive knowledge of the data-generating distribution. Existing results provide a comprehensive characterization when and why point estimates accurately recover behavior. this paper, develop flexible practical confidence intervals that asymptotic frequentist coverage estimands...

The purpose of this paper is to construct confidence intervals for the regression coefficients in high-dimensional Cox proportional hazards models where number covariates may be larger than sample size. Our debiased estimator construction similar those Zhang and (2014) van de Geer et al. (2014), but time-dependent censored risk sets introduce considerable additional challenges. theoretical resu...