Publication date
June 2017
DOIAbstract
We describe a non-parametric method based on the sole assumption that the data points form an i.i.d sample to compute confidence intervals for quantile
We describe a non-parametric method based on the sole assumption that the data points form an i.i.d sample to compute confidence intervals for quantile
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
An alternative (to profile likelihood techniques) to derive confidence intervals is to use the delta...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
We propose a new empirical likelihood approach which can be used to construct non-parametric (design...
Quantiles, which are also known as values-at-risk in finance, frequently arise in practice as measur...
Nonparametric techniques provide no analytical solutions for confidence intervals. The bootstrap and...
<p>Quantiles, which are also known as values-at-risk in finance, frequently arise in practice as mea...
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are...
It is shown how various exact nonparametric inferential procedures can be developed based on record ...
Quantiles and percentiles represent useful statistical tools for describing the distribution of resu...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
We propose a nonparametric method to construct confidence intervals for quantile marginal effects (i...
These procedures for forming confidence intervals are attractive because they require weaker assumpt...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
An alternative (to profile likelihood techniques) to derive confidence intervals is to use the delta...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
We propose a new empirical likelihood approach which can be used to construct non-parametric (design...
Quantiles, which are also known as values-at-risk in finance, frequently arise in practice as measur...
Nonparametric techniques provide no analytical solutions for confidence intervals. The bootstrap and...
<p>Quantiles, which are also known as values-at-risk in finance, frequently arise in practice as mea...
In this thesis, various construction methods for simultaneous confidence intervals for quantiles are...
It is shown how various exact nonparametric inferential procedures can be developed based on record ...
Quantiles and percentiles represent useful statistical tools for describing the distribution of resu...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
We propose a nonparametric method to construct confidence intervals for quantile marginal effects (i...
These procedures for forming confidence intervals are attractive because they require weaker assumpt...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
We describe and compare methods for constructing confidence intervals for quantile regression coeffi...
An alternative (to profile likelihood techniques) to derive confidence intervals is to use the delta...
Confidence intervals for the median of estimators or other quantiles were proposed as a substitute f...
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