summary:We consider the asymptotic distribution of covariate values in the quantile regression basic solution under weak assumptions. A diagnostic procedure for assessing homogeneity of the conditional densities is also proposed
We consider the problem of estimating quantile regression coefficients in errors-in-variables models...
For fixed α Ε 0, 1., the quantile regression function gives the α th quantile θ αx. in the condition...
Koenker & Basset, 1978 introduce the quantile regression estimator, that allows to have a more compl...
summary:We consider the asymptotic distribution of covariate values in the quantile regression basic...
This paper studies the asymptotic properties of the nonlinear quantile regression model under genera...
In the linear regression quantile model, the conditional quantile of the response, Y, given x is QY|...
To date the literature on quantile regression and least absolute deviation regression has assumed ei...
Regression quantiles have asymptotic variances that depend on the conditional densities of the respo...
We study the sampling properties of two alternative approaches to estimating the conditional distrib...
Allowing for misspecification in the linear conditional quantile function, this paper provides a new...
This paper introduces a nonparametric test for the correct specification of a linear conditional qua...
Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least square...
Quantile regression as introduced by Koenker and Bassett seeks to extend ideas of quantiles to the e...
This paper builds upon conditional quantile processes to develop methods for conducting uni-form inf...
We propose a notion of conditional vector quantile function and a vector quantile regression. A cond...
We consider the problem of estimating quantile regression coefficients in errors-in-variables models...
For fixed α Ε 0, 1., the quantile regression function gives the α th quantile θ αx. in the condition...
Koenker & Basset, 1978 introduce the quantile regression estimator, that allows to have a more compl...
summary:We consider the asymptotic distribution of covariate values in the quantile regression basic...
This paper studies the asymptotic properties of the nonlinear quantile regression model under genera...
In the linear regression quantile model, the conditional quantile of the response, Y, given x is QY|...
To date the literature on quantile regression and least absolute deviation regression has assumed ei...
Regression quantiles have asymptotic variances that depend on the conditional densities of the respo...
We study the sampling properties of two alternative approaches to estimating the conditional distrib...
Allowing for misspecification in the linear conditional quantile function, this paper provides a new...
This paper introduces a nonparametric test for the correct specification of a linear conditional qua...
Quantile regression(QR) fits a linear model for conditional quantiles, just as ordinary least square...
Quantile regression as introduced by Koenker and Bassett seeks to extend ideas of quantiles to the e...
This paper builds upon conditional quantile processes to develop methods for conducting uni-form inf...
We propose a notion of conditional vector quantile function and a vector quantile regression. A cond...
We consider the problem of estimating quantile regression coefficients in errors-in-variables models...
For fixed α Ε 0, 1., the quantile regression function gives the α th quantile θ αx. in the condition...
Koenker & Basset, 1978 introduce the quantile regression estimator, that allows to have a more compl...
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