Uniform in Bandwidth Consistency of the L1-Modal Regression Estimator for High-Dimensional Data [PDF]
EntropyWe propose a new nonparametric estimator of the conditional mode in a regression framework where the covariates are functional in nature. The estimator is constructed through a quantile regression approach, which provides a robust alternative to ...
Fatimah A. Almulhim +2 more
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Nonparametric Instrumental Variables Estimation of a Quantile Regression Model [PDF]
Econometrica, 2007 We consider nonparametric estimation of a regression function that is identified by requiring a specified quantile of the regression "error" conditional on an instrumental variable to be zero. The resulting estimating equation is a nonlinear integral equation of the first kind, which generates an ill-posed inverse problem.
Joel L Horowitz, Sokbae Lee
exaly +4 more sources
Ten-year trends and influencing factors of hospitalization costs in chronic obstructive pulmonary disease: a quantile regression analysis (2016–2025) [PDF]
Frontiers in Health ServicesBackgroundTo investigate the composition, temporal trends, and factors associated with per-admission hospitalization costs for chronic obstructive pulmonary disease (COPD)—related admissions from 2016 to 2025, adjusted for inflation and temporal effects,
Jieyun Zhu +9 more
doaj +2 more sources
Bootstrap-quantile ridge estimator for linear regression with applications.
PLoS ONEBootstrap is a simple, yet powerful method of estimation based on the concept of random sampling with replacement. The ridge regression using a biasing parameter has become a viable alternative to the ordinary least square regression model for the ...
Irum Sajjad Dar, Sohail Chand
doaj +2 more sources
Nonparametric Econometrics: The np Package [PDF]
Journal of Statistical Software, 2008 We describe the R np package via a series of applications that may be of interest to applied econometricians. The np package implements a variety of nonparametric and semiparametric kernel-based estimators that are popular among econometricians.
Tristen Hayfield, Jeffrey S. Racine
doaj +1 more source
Nonparametric screening for additive quantile regression in ultra-high dimension [PDF]
Journal of nonparametric statistics (Print), 2023 In practical applications, one often does not know the ‘true’ structure of the underlying conditional quantile function, especially in the ultra-high dimensional setting.
Daoji Li, Yinfei Kong, D. Zerom
semanticscholar +1 more source
Bayesian nonparametric quantile process regression and estimation of marginal quantile effects [PDF]
Biometrics, 2021 Flexible estimation of multiple conditional quantiles is of interest in numerous applications, such as studying the effect of pregnancy‐related factors on low and high birth weight.
Steven G. Xu, B. Reich
semanticscholar +1 more source
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction [PDF]
arXiv.org, 2022 We propose a nonparametric quantile regression method using deep neural networks with a rectified linear unit penalty function to avoid quantile crossing.
Wenlu Tang +3 more
semanticscholar +1 more source
Nonparametric Smoothing for Extremal Quantile Regression with Heavy Tailed Data
Revstat Statistical Journal, 2021 In several different fields, it is interested in analyzing the upper or lower tail quantile of the underlying distribution rather than mean or center quantile.
Takuma Yoshida
doaj +1 more source
How Do Financial Development and Renewable Energy Affect Consumption-Based Carbon Emissions?
Mathematical and Computational Applications, 2022 This paper bridges the gap in the literature by employing the novel quantile-on-quantile (QQ) approach, the quantile regression approach, and the nonparametric Granger causality test in quantiles to assess the effect of international trade on consumption-
Abraham Ayobamiji Awosusi +3 more
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