We discuss nonparametric estimation of conditional quantiles of a circular distribution when the conditioning variable is either linear or circular. Two different approaches are pursued: inversion of a conditional distribution function estimator, and minimization of a smoothed check function. Local constant and local linear versions of both estimators are discussed. Simulation experiments and a real data case study are used to illustrate the usefulness of the methods
We define a nonparametric prewhitening method for estimating conditional quantiles based on local li...
We have proposed a new LCDE method in circular-circular regression, where estimates are obtained fro...
In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the pr...
The conditional density offers the most informative summary of the relationship between explanatory ...
We study the sampling properties of two alternative approaches to estimating the conditional distrib...
[Abstract] Non-parametric regression with a circular response variable and a unidimensional linear r...
Learning about the shape of a probability distribution, not just about its location or dispersion, i...
Allowing for the existence of irrelevant covariates, we study the problem of estimating a conditiona...
Nonparametric density and regression estimation methods for circular data are included in the R pack...
In this paper, we investigate the problem of nonparametrically estimating a conditional quantile fun...
In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the pro...
Nonparametric density and regression estimation methods for circular data are included in the R pack...
Conditional quantile curves provide a comprehensive picture of a response contingent on explanatory ...
In this article we study nonparametric regression quantile estimation by kernel weighted local linea...
Quantile regression was originally introduced to the statistical community by Koenker and Basset ( [...
We define a nonparametric prewhitening method for estimating conditional quantiles based on local li...
We have proposed a new LCDE method in circular-circular regression, where estimates are obtained fro...
In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the pr...
The conditional density offers the most informative summary of the relationship between explanatory ...
We study the sampling properties of two alternative approaches to estimating the conditional distrib...
[Abstract] Non-parametric regression with a circular response variable and a unidimensional linear r...
Learning about the shape of a probability distribution, not just about its location or dispersion, i...
Allowing for the existence of irrelevant covariates, we study the problem of estimating a conditiona...
Nonparametric density and regression estimation methods for circular data are included in the R pack...
In this paper, we investigate the problem of nonparametrically estimating a conditional quantile fun...
In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the pro...
Nonparametric density and regression estimation methods for circular data are included in the R pack...
Conditional quantile curves provide a comprehensive picture of a response contingent on explanatory ...
In this article we study nonparametric regression quantile estimation by kernel weighted local linea...
Quantile regression was originally introduced to the statistical community by Koenker and Basset ( [...
We define a nonparametric prewhitening method for estimating conditional quantiles based on local li...
We have proposed a new LCDE method in circular-circular regression, where estimates are obtained fro...
In this paper a new nonparametric estimate of conditional quantiles is proposed, that avoids the pr...