Results 11 to 20 of about 3,477,506 (374)
Renewable Energy, 2021 Unlike previous studies examining the association between crude oil and renewable energy stock prices under average conditions, we employ a quantile-based regression approach offering a more comprehensive dependence structure under diverse market ...
Ishaan Dawar +3 more
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Journal of Economic Perspectives, 2001 Quantile regression, as introduced by Koenker and Bassett (1978), may be viewed as an extension of classical least squares estimation of conditional mean models to the estimation of an ensemble of models for several conditional quantile functions. The central special case is the median regression estimator which minimizes a sum of absolute errors ...
Koenker, Roger, Hallock, Kevin F.
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Quantile Regression with Generated Regressors
Econometrics, 2021 This paper studies estimation and inference for linear quantile regression models with generated regressors. We suggest a practical two-step estimation procedure, where the generated regressors are computed in the first step. The asymptotic properties of
Liqiong Chen +2 more
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Desimal, 2023 The censored quantile regression method is a parameter estimation method that can be used to overcome censored data and BLUE (Best Linear Unbiased Estimator) assumptions that are not met.
Sarmada Sarmada +2 more
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Modified Quantile Regression for Modeling the Low Birth Weight
Frontiers in Applied Mathematics and Statistics, 2022 This study aims to identify the best model of low birth weight by applying and comparing several methods based on the quantile regression method's modification.
Ferra Yanuar +2 more
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Ensemble Conformalized Quantile Regression for Probabilistic Time Series Forecasting [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2022 This article presents a novel probabilistic forecasting method called ensemble conformalized quantile regression (EnCQR). EnCQR constructs distribution-free and approximately marginally valid prediction intervals (PIs), which are suitable for ...
Vilde Jensen, F. Bianchi, S. N. Anfinsen
semanticscholar +1 more source
A Bayesian Binary reciprocal LASSO quantile regression (with practical application)
Journal of Kufa for Mathematics and Computer, 2023 Quantile regression is one of the methods that has taken a wide space in application in the previous two decades because of the attractive features of these methods to researchers, as it is not affected by outliers values, meaning that it is considered ...
Mohammed Kahnger, Ahmad Naeem Flaih
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Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021 This study aims to construct the model for the length of hospital stay for patients with COVID-19 using quantile regression and Bayesian quantile approaches.
Ferra Yanuar +4 more
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Pyramid Quantile Regression [PDF]
Journal of Computational and Graphical Statistics, 2019 Quantile regression models provide a wide picture of the conditional distributions of the response variable by capturing the effect of the covariates at different quantile levels. In most applications, the parametric form of those conditional distributions is unknown and varies across the covariate space, so fitting the given quantile levels ...
T. Rodrigues +2 more
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Fuzzy Semi-Parametric Logistic Quantile Regression Model
Wasit Journal for Pure Sciences, 2023 In this paper, the fuzzy semi-parametric logistic quantile regression model was studied in the absence of special conditions in the classical regression models.
Ahmed Razzaq, Ayad H. shemaila
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