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
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A plug-in bandwidth selector for nonparametric quantile regression [PDF]
Test, 2018 In the framework of quantile regression, local linear smoothing techniques have been studied by several authors, particularly by Yu and Jones (J Am Stat Assoc 93:228–237, 1998). The problem of bandwidth selection was addressed in the literature by the usual approaches, such as cross-validation or plug-in methods.
Cesar Sánchez-Sellero +1 more
exaly +3 more sources
Nonparametric quantile regression for twice censored data
Bernoulli, 2013 We consider the problem of nonparametric quantile regression for twice censored data. Two new estimates are presented, which are constructed by applying concepts of monotone rearrangements to estimates of the conditional distribution function. The proposed methods avoid the problem of crossing quantile curves.
Holger Dette, Stanislav Volgushev
exaly +6 more sources
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
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
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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
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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Nonparametric Quantile Regression for Homogeneity Pursuit in Panel Data Models [PDF]
Journal of Business & Economic Statistics, 2021 Many panel data have the latent subgroup effect on individuals, and it is important to correctly identify these groups since the efficiency of resulting estimators can be improved significantly by pooling the information of individuals within each group.
Xiaoyu Zhang +3 more
semanticscholar +1 more source