Results 221 to 230 of about 6,156 (248)

Non‐parametric Quantile Regression with Censored Data

Scandinavian Journal of Statistics, 2005
Abstract.  Censored regression models have received a great deal of attention in both the theoretical and applied statistics literature. Here, we consider a model in which the response variable is censored but not the covariates. We propose a new estimator of the conditional quantiles based on the local linear method, and give an algorithm for its ...
Saracco, Jérôme, Yuan, A., Bonney, G.E., Gannoun, Abdelmouhcine   +3 more
openaire   +2 more sources

A Bayesian Nonparametric Approach to Inference for Quantile Regression

Journal of Business & Economic Statistics, 2010
We develop a Bayesian method for nonparametric model–based quantile regression. The approach involves flexible Dirichlet process mixture models for the joint distribution of the response and the covariates, with posterior inference for different quantile curves emerging from the conditional response distribution given the covariates.
Taddy, Matthew A., Kottas, Athanasios
openaire   +2 more sources

Nonparametric extremal quantile regression

2013
Nonparametric regression quantiles obtained by inverting a kernel estimator of the conditional distribution of the response are long established in statistics [1,3,4]. Attention has been, however, restricted to ordinary quantiles staying away from the tails of the conditional distribution.
Daouia, Abdelaati, Gardes, Laurent, Girard, Stéphane   +2 more
openaire   +1 more source

Comparing Nonparametric Regression Quantiles [PDF]

, 2004
This paper investigates how conditional quantiles of a given distribution relate to each other. Given two conditional quantiles estimated nonparametrically, we investigate their relation by linking them through a parametric transformation. Asymptotic normality of the associated parameter vector is established, and the method is illustrated with data ...
openaire  

Quantile regression model for interval-censored data with competing risks

Journal of Applied Statistics
Our interest is to provide the methodology for estimating quantile regression model for interval-censored competing risk data. Lee and Kim [Analysis of interval censored competing risk data via nonparametric multiple imputation. Stat. Biopharm. Res.
Amirah Afiqah binti Che Ramli, Yang-Jin Kim   +1 more
semanticscholar   +1 more source

Nonparametric Testing of an Exclusion Restriction in Quantile Regression

Communications in Statistics - Theory and Methods, 2008
Using the framework proposed by Bickel et al. (2006), we provide a score-based testing method to check the exclusion restriction in quantile regression, i.e., H: να(Y|U, V) = να(Y|U) w.p.1, where να denotes the αth (0 
openaire   +1 more source

Short panel data quantile regression model with flexible correlated effects

Econometric Reviews
I propose an alternative linear model for short panel data quantile regression. The model assumes a nonparametric correlated effect (CE) that is τ-quantile-specific and time-invariant.
Doosoo Kim
semanticscholar   +1 more source

Nonparametric Quantile Regression Estimation With Mixed Discrete and Continuous Data

Journal of Business and Economic Statistics, 2021
Degui Li, Qi Li
exaly  

Nonparametric Quantile Regression for Homogeneity Pursuit in Panel Data Models

Journal of Business and Economic Statistics, 2023
Heng Lian, Guodong Li, Di Wang
exaly  

Cost-effective power system operation with nonparametric Probabilistic optimal power flow and quantile regression forests method

Signal, Image and Video Processing
Chengfu Sun, Chengyu Zhang
semanticscholar   +1 more source