The aim of the paper is to study the problem of estimating the quantile function of a finite population. Attention is first focused on point estimation, and asymptotic results are obtained. Confidence intervals are then constructed, based on both the following: (i) asymptotic results and (ii) a resampling technique based on rescaling the ‘usual’ bootstrap. A simulation study to compare asymptotic and resampling-based results, as well as an application to a real population, is finally performed
78 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Improved estimates of a survey...
We consider quantile estimation using Markov chain Monte Carlo and establish con-ditions under which...
The asymptotic variance matrix of the quantile regression estimator depends on the density of the er...
The aim of the paper is to study the problem of estimating the quantile function of a finite populati...
Confidence intervals provide a way of reporting an estimate of a population quantile along with some...
In sampling finite populations, several resampling schemes have been proposed. The common starting p...
The goal of our research is to estimate the quantiles of a distribution from a large set of samples ...
Under minimal assumptions, finite sample confidence bands for quantile regression models can be cons...
In this paper, a class of resampling techniques for finite populations under πps sampling design is ...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is ess...
Abstract: A quantile model-assisted approach is used to estimate a finite population total. This e...
We consider estimation of a quantile from a discrete distribution. This gives rise to three new idea...
Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems ...
In sampling finite populations, several resampling schemes have been proposed. The common starting po...
This paper evaluates bootstrap inference methods for quantile regression panel data models. We propo...
78 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Improved estimates of a survey...
We consider quantile estimation using Markov chain Monte Carlo and establish con-ditions under which...
The asymptotic variance matrix of the quantile regression estimator depends on the density of the er...
The aim of the paper is to study the problem of estimating the quantile function of a finite populati...
Confidence intervals provide a way of reporting an estimate of a population quantile along with some...
In sampling finite populations, several resampling schemes have been proposed. The common starting p...
The goal of our research is to estimate the quantiles of a distribution from a large set of samples ...
Under minimal assumptions, finite sample confidence bands for quantile regression models can be cons...
In this paper, a class of resampling techniques for finite populations under πps sampling design is ...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is ess...
Abstract: A quantile model-assisted approach is used to estimate a finite population total. This e...
We consider estimation of a quantile from a discrete distribution. This gives rise to three new idea...
Sample quantiles are consistent estimators for the true quantile and satisfy central limit theorems ...
In sampling finite populations, several resampling schemes have been proposed. The common starting po...
This paper evaluates bootstrap inference methods for quantile regression panel data models. We propo...
78 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.Improved estimates of a survey...
We consider quantile estimation using Markov chain Monte Carlo and establish con-ditions under which...
The asymptotic variance matrix of the quantile regression estimator depends on the density of the er...