Estimation for Extreme Conditional Quantiles of Functional Quantile Regression
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Publication:5041331
DOI10.5705/ss.202020.0487OpenAlexW4200136187MaRDI QIDQ5041331
Ri-quan Zhang, Weixin Yao, Yehua Li, Hanbing Zhu
Publication date: 13 October 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202020.0487
extrapolationheavy-tailed distributionextreme value theoryfunctional principal component analysisextreme quantilefunctional quantile regression
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Cites Work
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- Automated threshold selection for extreme value analysis via ordered goodness-of-fit tests with adjustment for false discovery rate
- Estimation of extreme conditional quantiles through an extrapolation of intermediate regression quantiles
- Inference for single-index quantile regression models with profile optimization
- Estimating the conditional tail index by integrating a kernel conditional quantile estimator
- Recent advances in functional data analysis and related topics. Selected papers based on the presentations at the international workshop on functional and operatorial statistics (IWFOS'2011), Santander, Spain, June 16--18, 2011.
- Conditional extremes from heavy-tailed distributions: an application to the estimation of extreme rainfall return levels
- Estimation in functional linear quantile regression
- Using the bootstrap to estimate mean squared error and select smoothing parameter in nonparametric problems
- Prediction in functional linear regression
- Adaptive estimation of heavy right tails: resampling-based methods in action
- Composite quantile regression and the oracle model selection theory
- Methodology and convergence rates for functional linear regression
- A simple general approach to inference about the tail of a distribution
- TPRM: tensor partition regression models with applications in imaging biomarker detection
- Estimation and testing for partially functional linear errors-in-variables models
- Tail dimension reduction for extreme quantile estimation
- Detecting change-points in extremes
- How to make a Hill plot.
- Quantile regression for longitudinal data
- Predicting extreme value at risk: nonparametric quantile regression with refinements from extreme value theory
- Functional kernel estimators of large conditional quantiles
- Longitudinal functional principal component analysis
- Extremal quantile treatment effects
- Extremal quantile regression
- Regularized partially functional quantile regression
- New efficient estimation and variable selection methods for semiparametric varying-coefficient partially linear models
- Functional data analysis.
- Fast covariance estimation for high-dimensional functional data
- A Diagnostic for Selecting the Threshold in Extreme Value Analysis
- Classical testing in functional linear models
- Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks
- Regression Quantiles
- Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
- Tail Index Estimation, Pareto Quantile Plots, and Regression Diagnostics
- Conditional Quantile Analysis When Covariates are Functions, with Application to Growth Data
- Estimation of High Conditional Quantiles for Heavy-Tailed Distributions
- Spatially Varying Coefficient Model for Neuroimaging Data With Jump Discontinuities
- Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
- Selecting the Number of Principal Components in Functional Data
- Inference on the Quantile Regression Process
- Quantile regression when the covariates are functions
- Functional Data Analysis for Sparse Longitudinal Data
- Extreme Value Theory and Statistics of Univariate Extremes: A Review