This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for … and does not depend on the sampling schemes. It is based upon projection of simultaneous confidence bands for distribution … rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions. …

This paper provides a method to construct simultaneous confidence bands for quantile and quantile effect functions for … and does not depend on the sampling schemes. It is based upon projection of simultaneous confidence bands for distribution … rendering standard inference methods invalid for obtaining uniform confidence bands for quantile and quantile effects functions. …

model. Any method for constructing a confidence interval or band for this function must deal with the asymptotic bias of … used to obtain uniform confidence bands. The bootstrap method uses only bandwidths that are selected by standard methods …

methods to three empirical studies. We find that the confidence intervals based on estimators of the correct variance may … differences in confidence intervals concern economically meaningful values of mobility and thus lead to different conclusions when …

estimating and constructing confidence regions for a regression parameter of primary interest α0, a parameter in front of the … regression function, where s is smaller than n. Importantly, the estimators and these resulting confidence regions are "honest …

We develop uniformly valid confidence regions for regression coefficients in a high-dimensional sparse least absolute … confidence regions are valid uniformly with respect to the underlying model. We illustrate the value of uniformity with Monte … a single target regression coefficient as a very special case. We construct simultaneous confidence bands on all p1 …

it allows for imperfect slection of the controls and provides confidence intervals that are valid uniformly across a …

We develop uniformly valid confidence regions for a regression coefficient in a high-dimensional sparse LAD (least … root-n normal uniformly with respect to the underlying sparse model. The resulting confidence regions are vaild uniformly …

it allows for imperfect selection of the controls and provides confidence intervals that are valid uniformly across a …