We give methods for the construction of designs for regression models, when the purpose of the investigation is the estimation of the conditional quantile function, and the estimation method is quantile regression. The designs are robust against misspecified response functions, and against unanticipated heteroscedasticity. The methods are illustrated by example, and in a case study in which they are applied to growth charts
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
The article considers a test of specification for quantile regressions. The test relies on the incre...
The thesis consists of six chapters and focus on two topics: quantile regression and survival analys...
We give methods for the construction of designs for regression models, when the purpose of the inves...
We give methods for the construction of designs for regression models, when the purpose of the inves...
Volume two of Quantile Regression offers an important guide for applied researchers that draws on th...
Volume two of Quantile Regression offers an important guide for applied researchers that draws on th...
A new, broad family of quantile-based estimators is described, and theoretical and empirical evidenc...
Quantile regression, as introduced by Koenker and Bassett (1978), may be viewed as an extension of c...
Quantile regression offers a more complete statistical model than mean regression and now has widesp...
Koenker & Basset, 1978 introduce the quantile regression estimator, that allows to have a more compl...
Quantile regression provides a method for estimating quantiles of a distribution while incorporating...
A guide to the implementation and interpretation of Quantile Regression models. This book explores t...
Quantile regression model has caught a lot of attention lately in many areas including statistics an...
Modeling quantile regression coefficients functions permits describing the coefficients of a quanti...
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
The article considers a test of specification for quantile regressions. The test relies on the incre...
The thesis consists of six chapters and focus on two topics: quantile regression and survival analys...
We give methods for the construction of designs for regression models, when the purpose of the inves...
We give methods for the construction of designs for regression models, when the purpose of the inves...
Volume two of Quantile Regression offers an important guide for applied researchers that draws on th...
Volume two of Quantile Regression offers an important guide for applied researchers that draws on th...
A new, broad family of quantile-based estimators is described, and theoretical and empirical evidenc...
Quantile regression, as introduced by Koenker and Bassett (1978), may be viewed as an extension of c...
Quantile regression offers a more complete statistical model than mean regression and now has widesp...
Koenker & Basset, 1978 introduce the quantile regression estimator, that allows to have a more compl...
Quantile regression provides a method for estimating quantiles of a distribution while incorporating...
A guide to the implementation and interpretation of Quantile Regression models. This book explores t...
Quantile regression model has caught a lot of attention lately in many areas including statistics an...
Modeling quantile regression coefficients functions permits describing the coefficients of a quanti...
Quantile regression extends ordinary least-squares regression to quantiles of the response variable....
The article considers a test of specification for quantile regressions. The test relies on the incre...
The thesis consists of six chapters and focus on two topics: quantile regression and survival analys...