Dimension reduction techniques for conditional expectiles
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Publication:6132713
DOI10.1080/02331888.2023.2236745OpenAlexW4384695028MaRDI QIDQ6132713
Publication date: 17 August 2023
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2023.2236745
Cites Work
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- Measuring and testing dependence by correlation of distances
- Asymmetric Least Squares Estimation and Testing
- Assessing value at risk with CARE, the conditional autoregressive expectile models
- Geoadditive expectile regression
- Principal support vector machines for linear and nonlinear sufficient dimension reduction
- On confidence intervals for semiparametric expectile regression
- Nonparametric estimates of regression quantiles and their local Bahadur representation
- Variable selection in high-dimensional linear model with possibly asymmetric errors
- Successive direction extraction for estimating the central subspace in a multiple-index regres\-sion
- Optimal expectile smoothing
- Asymptotic properties of kernel estimators based on local medians
- Expectiles and \(M\)-quantiles are quantiles
- Conditional expectiles, time consistency and mixture convexity properties
- Generalized quantiles as risk measures
- Kernel sliced inverse regression: regularization and consistency
- Asymptotics of graphical projection pursuit
- Central quantile subspace
- Sequential change point detection in linear quantile regression models
- On efficient dimension reduction with respect to a statistical functional of interest
- Theoretical foundations of the potential function method in pattern recognition learning
- Nonlinear dimension reduction for conditional quantiles
- Transformed sufficient dimension reduction
- 10.1162/153244303768966085
- An Effective Bandwidth Selector for Local Least Squares Regression
- UNIFORM BIAS STUDY AND BAHADUR REPRESENTATION FOR LOCAL POLYNOMIAL ESTIMATORS OF THE CONDITIONAL QUANTILE FUNCTION
- Nonparametric regression expectiles∗
- M-quantiles
- Local Linear Quantile Regression
- Sliced Inverse Regression for Dimension Reduction
- On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function
- Regression Quantiles
- Asymmetric least squares regression estimation: A nonparametric approach∗
- Bahadur representation and its applications for local polynomial estimates in nonparametric M -regression
- Nonparametric conditional autoregressive expectile model via neural network with applications to estimating financial risk
- Beyond mean regression
- Discussion: The beauty of expectiles
- Discussion: Living beyond our means
- Expectile and quantile regression—David and Goliath?
- Transformed central quantile subspace
- Nonparametric multiple expectile regression via ER-Boost
- Dimension Reduction in Regressions Through Cumulative Slicing Estimation
- Theory of Reproducing Kernels
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