bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function … mean and variance have been derived. Given a closed-form expression for the bias, bias-corrected estimator of the …-parametric and easy to implement. Our approach can be connected to corrections for selection bias and shrinkage estimation and is to …

asymptotic linear expansions with nearly optimal rates. Second, we study the higher-order bias of exact quantile estimators up to … O (1/n). Using a novel non-smooth calculus technique, we uncover previously unknown non-negligible bias components that … "symmetric" bias correction, which admits a feasible implementation. Our simulations confirm the empirical importance of bias …

bias in the empirical distribution arising from the presence of noise. The leading bias in the empirical quantile function … for selection bias and shrinkage estimation and is to be contrasted with deconvolution. Simulation results confirm the …

suffer of incidental parameter bias. We show how models with factor structures can also be applied to capture important …