Copertina

Gaussian Approximation for High-Dimensional Second-Order $U$- and $V$-statistics with Size-Dependent Kernels under i.n.i.d. Sampling

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Imai, Shunsuke
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Statistics Theory
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Gaussian Approximation for High-Dimensional $U$-statistics with Size-Dependent Kernels
di: Imai, Shunsuke, et al.
Pubblicazione: (2025)

An exponential inequality for Hilbert-valued U-statistics of i.i.d. data
di: Giraudo, Davide
Pubblicazione: (2024)

Slow rates of approximation of U-statistics and V-statistics by quadratic forms of Gaussians
di: Huang, Kevin Han, et al.
Pubblicazione: (2024)

Sparse estimation for the drift of high-dimensional Ornstein--Uhlenbeck processes with i.i.d. paths
di: Nakakita, Shogo
Pubblicazione: (2025)

Tracy-Widom, Gaussian, and Bootstrap: Approximations for Leading Eigenvalues in High-Dimensional PCA
di: Dörnemann, Nina, et al.
Pubblicazione: (2025)

On Second-Order Statistics of the Log-Average Periodogram for Gaussian Processes
di: Klockmann, Karolina, et al.
Pubblicazione: (2023)

Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders
di: Yan, Jian, et al.
Pubblicazione: (2021)

Order-Explicit Linearization of High-Dimensional $U$-Statistics
di: Ritzwoller, David M., et al.
Pubblicazione: (2024)

The Empirical Spectral Distribution of i.i.d. Random Matrices with Random Perturbations
di: Chen, Kun, et al.
Pubblicazione: (2024)

High Order Expansion Method for Kuiper's $V_n$ Statistic in Goodness-of-fit Test
di: Zhang, Hong-Yan, et al.
Pubblicazione: (2023)

Strong Gaussian approximation for U-statistics in high dimensions and beyond
di: Li, Weijia, et al.
Pubblicazione: (2026)

Composite goodness-of-fit test with the Kernel Stein Discrepancy and a bootstrap for degenerate U-statistics with estimated parameters
di: Brück, Florian, et al.
Pubblicazione: (2025)

Singularity-agnostic incomplete U-statistics for testing polynomial constraints in Gaussian covariance matrices
di: Leung, Dennis, et al.
Pubblicazione: (2024)

Sub-Gaussian High-Dimensional Covariance Matrix Estimation under Elliptical Factor Model with 2 + εth Moment
di: Ding, Yi, et al.
Pubblicazione: (2024)

Sample Path Regularity of Gaussian Processes from the Covariance Kernel
di: Da Costa, Nathaël, et al.
Pubblicazione: (2023)

U-statistics of local sample moments under weak dependence
di: Dehling, Herold G., et al.
Pubblicazione: (2023)

Sharp One-Dimensional Sub-Gaussian Comparison in Convex Order
di: Zhang, Yihan
Pubblicazione: (2026)

High Dimensional Logistic Regression Under Network Dependence
di: Mukherjee, Somabha, et al.
Pubblicazione: (2021)

A Kernel Two-Sample Test Invariant under Group Action with Applications to Functional Data
di: Giacofci, Madison, et al.
Pubblicazione: (2026)

Nearest-Neighbor Radii under Dependent Sampling
di: Gao, Yuanyuan, et al.
Pubblicazione: (2026)

Wasserstein and Convex Gaussian Approximations for Non-stationary Time Series of Diverging Dimensionality
di: Liu, Miaoshiqi, et al.
Pubblicazione: (2025)

On Gaussian Approximation for M-Estimator
di: Imaizumi, Masaaki, et al.
Pubblicazione: (2020)

High-Dimensional Gaussian Mean Estimation under Realizable Contamination
di: Diakonikolas, Ilias, et al.
Pubblicazione: (2026)

Universality of High-Dimensional Logistic Regression and a Novel CGMT under Dependence with Applications to Data Augmentation
di: Mallory, Matthew Esmaili, et al.
Pubblicazione: (2025)

Estimation of Out-of-Sample Sharpe Ratio for High Dimensional Portfolio Optimization
di: Meng, Xuran, et al.
Pubblicazione: (2024)

Structured Matrix Learning under Arbitrary Entrywise Dependence and Estimation of Markov Transition Kernel
di: Chai, Jinhang, et al.
Pubblicazione: (2024)

Second-order PACF asymptotics and discrimination between fractional Gaussian noise and $\FARIMA(0,d,0)$
di: Cai, Chunhao
Pubblicazione: (2026)

Dependency-Aware Shrinkage Priors for High Dimensional Regression
di: Aguilar, Javier Enrique, et al.
Pubblicazione: (2025)

Statistical Inference on High Dimensional Gaussian Graphical Regression Models
di: Meng, Xuran, et al.
Pubblicazione: (2024)

On the Approximation Accuracy of Gaussian Variational Inference
di: Katsevich, Anya, et al.
Pubblicazione: (2023)

Recursive Neyman Algorithm for Optimum Sample Allocation under Box Constraints on Sample Sizes in Strata
di: Wesołowski, Jacek, et al.
Pubblicazione: (2023)

Another look at Stein's method for Studentized nonlinear statistics with an application to U-statistics
di: Leung, Dennis, et al.
Pubblicazione: (2023)

Error Bounds for a Kernel-Based Constrained Optimal Smoothing Approximation
di: Grammont, Laurence, et al.
Pubblicazione: (2024)

On High Dimensional Behaviour of Some Two-Sample Tests Based on Ball Divergence
di: Banerjee, Bilol, et al.
Pubblicazione: (2022)

Two-Sample Covariance Inference in High-Dimensional Elliptical Models
di: Dörnemann, Nina
Pubblicazione: (2025)

Gaussian Multiplier Bootstrap Procedure for the $k$th Largest Coordinate of High-Dimensional Statistics
di: Ding, Yixi, et al.
Pubblicazione: (2025)

Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
di: Balasubramanian, Krishnakumar, et al.
Pubblicazione: (2025)

Sequential Multiple Testing: A Second-Order Asymptotic Analysis
di: Liu, Jingyu, et al.
Pubblicazione: (2026)

Evolving privacy: drift parameter estimation for discretely observed i.i.d. diffusion processes under LDP
di: Amorino, Chiara, et al.
Pubblicazione: (2024)

High-Dimensional Covariate-Dependent Discrete Graphical Models and Dynamic Ising Models
di: Roach, Lyndsay, et al.
Pubblicazione: (2025)