Bootstrap Inference for Quantile-based Modal Regression
From MaRDI portal
Publication:6107195
DOI10.1080/01621459.2021.1918130zbMath1514.62069arXiv2006.00952OpenAlexW3155054572MaRDI QIDQ6107195
Tao Zhang, David Ruppert, Kengo Kato
Publication date: 3 July 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.00952
Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Nonparametric statistical resampling methods (62G09)
Cites Work
- Unnamed Item
- Nonparametric modal regression
- Empirical and multiplier bootstraps for suprema of empirical processes of increasing complexity, and related Gaussian couplings
- Gaussian approximation of suprema of empirical processes
- Some new asymptotic theory for least squares series: pointwise and uniform results
- Bayesian mode regression using mixtures of triangular densities
- Regression towards the mode
- Mode regression
- Extremes and related properties of random sequences and processes
- Censored regression quantiles
- Maximum likelihood estimation of isotonic modal regression
- Subsampling
- Quadratic mode regression
- Jackknife multiplier bootstrap: finite sample approximations to the \(U\)-process supremum with applications
- Convergence rates of least squares regression estimators with heavy-tailed errors
- Quantile regression approach to conditional mode estimation
- Conditional quantile processes based on series or many regressors
- Central limit theorems and bootstrap in high dimensions
- Finite sample inference for quantile regression models
- A New Regression Model: Modal Linear Regression
- Non linear parametric mode regression
- Local modal regression
- Regression Quantiles
- Asymptotic Statistics
- A resampling method based on pivotal estimating functions
- A Statistical Learning Approach to Modal Regression
- Semi‐linear mode regression
- Instrumental Variable Treatment of Nonclassical Measurement Error Models
- Modelling Beyond Regression Functions: An Application of Multimodal Regression to Speed–Flow Data