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An Algorithm of Nonparametric Quantile Regression
Journal of Statistical Theory and Practice, 2023 Extreme events, such as earthquakes, tsunamis, and market crashes, can have substantial impact on social and ecological systems. Quantile regression can be used for predicting these extreme events, making it an important problem that has applications in many fields. Estimating high conditional quantiles is a difficult problem.
Mei Ling Huang, William Marshall
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Nonparametric inference on smoothed quantile regression process
Computational Statistics & Data Analysis, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Meiling Hao +3 more
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Quantile regression: a nonparametric approach
Computational Statistics and Data Analysis, 1988Abstract Regression on any p -th quantile is considered through nonparametric modelling. The nonparametric technique used is moving parabolic fit which is known to be adaptative and to reduce bias in the usual mean regression. The quantile problem reduces to solving weighted linear regression in L 1 norm at each x -point and the iteratively ...
Michel G. Lejeune, Pascal Sarda
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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.
Sokbae Lee
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On nonparametric regression estimators based on regression quantiles
Communications in Statistics - Theory and Methods, 1987In the ciassical regression model Yi=h(xi) + ∊ i, i=1,…,n, Cheng (1984) introduced linear combinations of regression quantiles as a new class of estimators for the unknown regression function h(x). The asymptotic properties studied in Cheng (1984) are reconsidered.
P Janssen, N Veraverbeke
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Nonparametric regression M-quantiles
Statistics & Probability Letters, 1989zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Antoch, J., Janssen, P.
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Nonparametric quantile scalar-on-image regression
Computational Statistics & Data AnalysiszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chuchu Wang, Xinyuan Song
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Local asymptotics for nonparametric quantile regression with regression splines
Statistics & Probability Letters, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Weihua, Lian, Heng
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Variational Inference for Nonparametric Bayesian Quantile Regression
Proceedings of the AAAI Conference on Artificial Intelligence, 2015Quantile regression deals with the problem of computing robust estimators when the conditional mean and standard deviation of the predicted function are inadequate to capture its variability. The technique has an extensive list of applications, including health sciences, ecology and finance.
Sachinthaka Abeywardana +1 more
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