Confidence intervals provide a way of reporting an estimate of a population quantile along with some information about the precision of estimates. Some procedures that may be used to obtain estimates of confidence intervals for quantiles in a finite population (most of which are based on resampling) are compared in the paper. A simulation study, based on two different artificial populations, is performed and comparisons of the estimation methods proposed for confidence intervals of population quantiles are made. First Published Online: 14 Oct 201
This article is concerned with the calculation of confidence intervals for simulation output that is...
The likelihood ratio method is used to construct a confidence interval for a population mean when sa...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is ess...
Confidence intervals provide a way of reporting an estimate of a population quantile along with some...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
For any estimate of response, confidence intervals are important as they help quantify a plausible r...
Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructi...
The aim of the paper is to study the problem of estimating the quantile function of a finite populat...
A method for estimating quantiles and their confidence intervals based on the paper by Francisco-Ful...
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
The aim of the paper is to study the problem of estimating the quantile function of a finite populati...
Quantiles and percentiles represent useful statistical tools for describing the distribution of resu...
We propose a new empirical likelihood approach which can be used to construct non-parametric (design...
A confidence interval is a standard way of expressing our uncertainty about the value of a populatio...
This article is concerned with the calculation of confidence intervals for simulation output that is...
The likelihood ratio method is used to construct a confidence interval for a population mean when sa...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is ess...
Confidence intervals provide a way of reporting an estimate of a population quantile along with some...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
For any estimate of response, confidence intervals are important as they help quantify a plausible r...
Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructi...
The aim of the paper is to study the problem of estimating the quantile function of a finite populat...
A method for estimating quantiles and their confidence intervals based on the paper by Francisco-Ful...
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
The aim of the paper is to study the problem of estimating the quantile function of a finite populati...
Quantiles and percentiles represent useful statistical tools for describing the distribution of resu...
We propose a new empirical likelihood approach which can be used to construct non-parametric (design...
A confidence interval is a standard way of expressing our uncertainty about the value of a populatio...
This article is concerned with the calculation of confidence intervals for simulation output that is...
The likelihood ratio method is used to construct a confidence interval for a population mean when sa...
A resampling technique for probability-proportional-to size sampling designs is proposed. It is ess...