Measuring and testing for interval quantile dependence
From MaRDI portal
Publication:1991673
DOI10.1214/17-AOS1635zbMath1408.62087MaRDI QIDQ1991673
Kai Xu, Li-ping Zhu, Yaowu Zhang
Publication date: 30 October 2018
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.aos/1536307230
Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Measures of association (correlation, canonical correlation, etc.) (62H20)
Related Items (2)
Local dependence test between random vectors based on the robust conditional Spearman's \(\rho\) and Kendall's \(\tau\) ⋮ Rank-based indices for testing independence between two high-dimensional vectors
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Measuring and testing dependence by correlation of distances
- Model-Free Feature Screening for Ultrahigh-Dimensional Data
- Sure independence screening in generalized linear models with NP-dimensionality
- Partial martingale difference correlation
- Robust rank correlation based screening
- Globally adaptive quantile regression with ultra-high dimensional data
- Brownian distance covariance
- Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
- A consistent test of independence based on a sign covariance related to Kendall's tau
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
- L-Estimation for Linear Models
- Hypothesis Testing When a Nuisance Parameter is Present Only Under the Alternative
- Regression Quantiles
- Inconsistency of the Bootstrap when a Parameter is on the Boundary of the Parameter Space
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Feature Screening via Distance Correlation Learning
- Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening
- Conditional quantile screening in ultrahigh-dimensional heterogeneous data
- Quantile Correlations and Quantile Autoregressive Modeling
- An Adaptive Resampling Test for Detecting the Presence of Significant Predictors
- A consistent multivariate test of association based on ranks of distances
- Distribution Free Tests of Independence Based on the Sample Distribution Function
- Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
This page was built for publication: Measuring and testing for interval quantile dependence