The functional \(k\mathrm{NN}\) estimator of the conditional expectile: uniform consistency in number of neighbors
From MaRDI portal
Publication:2076038
DOI10.1515/strm-2019-0029zbMath1493.62151OpenAlexW3205327183MaRDI QIDQ2076038
Ali Laksaci, Zouaoui Chikr Elmezouar, Ibrahim M. Almanjahie, Salim Bouzebda
Publication date: 18 February 2022
Published in: Statistics \& Risk Modeling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/strm-2019-0029
functional data analysisexpectile regression\(k\mathrm{NN}\) methodalmost complete convergence ratefunctional nonparametric statisticsUNN consistency
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)
Related Items (4)
The \(k\)-nearest neighbors method in single index regression model for functional quasi-associated time series data ⋮ Weak-convergence of empirical conditional processes and conditional \(U\)-processes involving functional mixing data ⋮ Uniform consistency and uniform in number of neighbors consistency for nonparametric regression estimates and conditional \(U\)-statistics involving functional data ⋮ Local linear estimate of the functional expectile regression
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Asymmetric Least Squares Estimation and Testing
- Relative-error prediction in nonparametric functional statistics: theory and practice
- Assessing value at risk with CARE, the conditional autoregressive expectile models
- Expectile asymptotics
- Asymptotic results for an \(L^1\)-norm kernel estimator of the conditional quantile for functional dependent data with application to climatology
- Uniform consistency of \(k\mathrm{NN}\) regressors for functional variables
- Inference for functional data with applications
- Geoadditive expectile regression
- U-processes: Rates of convergence
- Learning rates for kernel-based expectile regression
- Lectures on the nearest neighbor method
- On robust nonparametric regression estimation for a functional regressor
- Expectiles and \(M\)-quantiles are quantiles
- Convex measures of risk and trading constraints
- Expectile regression for analyzing heteroscedasticity in high dimension
- Editorial for the special issue on functional data analysis and related topics
- Conditional expectiles, time consistency and mixture convexity properties
- A note on prediction via estimation of the conditional mode function
- Relating quantiles and expectiles under weighted-symmetry
- Weak convergence and empirical processes. With applications to statistics
- Generalized quantiles as risk measures
- Tail expectile process and risk assessment
- Backtesting VaR and expectiles with realized scores
- Data-driven \(k\)NN estimation in nonparametric functional data analysis
- Introduction to empirical processes and semiparametric inference
- Functional data analysis.
- Nonparametric functional data analysis. Theory and practice.
- Uniform in bandwidth consistency of kernel-type function estimators
- The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data
- COHERENCE AND ELICITABILITY
- Recursive kernel estimate of the conditional quantile for functional ergodic data
- Nonparametric regression expectiles∗
- k-Nearest Neighbour method in functional nonparametric regression
- M-quantiles
- On the Estimation of Production Frontiers: Maximum Likelihood Estimation of the Parameters of a Discontinuous Density Function
- Uniform Central Limit Theorems
- A family of minimax rates for density estimators in continuous time
- Nonparametric modelling for functional data: selected survey and tracks for future
- NONPARAMETRIC ESTIMATION OF CONDITIONAL VALUE-AT-RISK AND EXPECTED SHORTFALL BASED ON EXTREME VALUE THEORY
- Estimation of Tail Risk Based on Extreme Expectiles
- FDA: strong consistency of the kNN local linear estimation of the functional conditional density and mode
- Beyond mean regression
- Uniform in bandwidth consistency for various kernel estimators involving functional data
- Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet Representations and Forecast Rankings
- Statistical Inference for Expectile‐based Risk Measures
- Conditional VAR and Expected Shortfall: A New Functional Approach
- Convergence of stochastic processes
This page was built for publication: The functional \(k\mathrm{NN}\) estimator of the conditional expectile: uniform consistency in number of neighbors
