Cover Image

Robust mean change point testing in high-dimensional data with heavy tails

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Mengchu, Chen, Yudong, Wang, Tengyao, Yu, Yi
Format:	Preprint
Published:	2023
Subjects:	Statistics Theory Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Residual permutation test for regression coefficient testing
by: Wen, Kaiyue, et al.
Published: (2022)

Detecting change regions on spheres
by: Su, Di, et al.
Published: (2026)

On the universal calibration of heavy-tailed combination tests
by: Chakraborty, Parijat, et al.
Published: (2025)

Covariance scanning for adaptively optimal change point detection in high-dimensional linear models
by: Cho, Haeran, et al.
Published: (2025)

Testing common structure in high-dimensional factor models: change-point and two-sample procedures
by: Düker, Marie-Christine, et al.
Published: (2024)

A nonparametric test of spherical symmetry applicable to high dimensional data
by: Banerjee, Bilol, et al.
Published: (2024)

Adaptive L-statistics for high dimensional test problem
by: Ma, Huifang, et al.
Published: (2024)

Exact distribution-free tests of spherical symmetry applicable to high dimensional data
by: Banerjee, Bilol, et al.
Published: (2024)

Robust Inference for High-dimensional Linear Models with Heavy-tailed Errors via Partial Gini Covariance
by: Zhang, Yilin, et al.
Published: (2024)

Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning
by: Guo, Zijian, et al.
Published: (2022)

Non-parametric estimation of conditional quantiles for time series with heavy tails
by: Mathew, Deemat C, et al.
Published: (2024)

Test for high-dimensional mean vectors via the weighted $L_2$-norm
by: Li, Jianghao, et al.
Published: (2024)

Detection and inference of changes in high-dimensional linear regression with non-sparse structures
by: Cho, Haeran, et al.
Published: (2024)

Catoni-style confidence sequences for heavy-tailed mean estimation
by: Wang, Hongjian, et al.
Published: (2022)

Detection of mean changes in partially observed functional data
by: Hudecová, Šárka, et al.
Published: (2025)

Federated Transfer Learning with Differential Privacy
by: Li, Mengchu, et al.
Published: (2024)

Robust estimation for high-dimensional time series with heavy tails
by: Wang, Yu, et al.
Published: (2024)

Multiple change point detection in functional data with applications to biomechanical fatigue data
by: Bastian, Patrick, et al.
Published: (2023)

Transfer learning for piecewise-constant mean estimation: Optimality, $\ell_1$- and $\ell_0$-penalisation
by: Wang, Fan, et al.
Published: (2023)

Mitigating dimensionality effects with robust graph constructions for testing
by: Zhu, Yejiong, et al.
Published: (2023)

Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
by: Chang, Jinyuan, et al.
Published: (2018)

Testing independence in the presence of missing data: high-dimensional case
by: Cuparić, Marija, et al.
Published: (2026)

Deep neural expected shortfall regression with tail-robustness
by: Yu, Myeonghun, et al.
Published: (2025)

A spectral approach for online covariance change point detection
by: Bao, Zhigang, et al.
Published: (2026)

Trends in tail dependence of heteroscedastic extremes
by: Einmahl, John H. J., et al.
Published: (2026)

Latent confounding in high-dimensional nonlinear models
by: Wang, Yuhao, et al.
Published: (2025)

Dimension estimation in PCA model using high-dimensional data augmentation
by: Radojicic, Una, et al.
Published: (2025)

Uncertainty of high-dimensional genetic data prediction with polygenic risk scores
by: Fu, Haoxuan, et al.
Published: (2024)

On goodness-of-fit testing for self-exciting point processes
by: Kling, José C. F., et al.
Published: (2024)

Differentially private hypothesis testing in survival analysis
by: Hung, Elly K. H., et al.
Published: (2026)

Practically significant change points in high dimension -- measuring signal strength pro active component
by: Quanz, Pascal, et al.
Published: (2025)

Higher-criticism for sparse multi-stream change-point detection
by: Gong, Tingnan, et al.
Published: (2024)

Power of masking methods for adaptive testing in a multivariate normal means problem
by: Chakraborty, Abhinav, et al.
Published: (2026)

An autocovariance-based learning framework for high-dimensional functional time series
by: Chang, Jinyuan, et al.
Published: (2020)

Asymmetric canonical correlation analysis of Riemannian and high-dimensional data
by: Buenfil, James, et al.
Published: (2024)

Weight-calibrated estimation for factor models of high-dimensional time series
by: Qiao, Xinghao, et al.
Published: (2025)

Coverage correlation: detecting singular dependencies between random variables
by: Yang, Xuzhi, et al.
Published: (2025)

Simultaneous hypothesis testing for comparing many functional means
by: Decker, Colin, et al.
Published: (2025)

Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates
by: Lu, Xin, et al.
Published: (2023)

Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
by: Liu, Lin, et al.
Published: (2023)