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In survival studies, classical inferences for left-truncated data require quasi-independence, a property that the joint density of truncation time and failure time is factorizable into their marginal densities in the observable region. The…

Methodology · Statistics 2019-04-16 Young-Geun Choi , Wei-Yann Tsai , Myunghee Cho Paik

In testing of hypothesis the robustness of the tests is an important concern. Generally, the maximum likelihood based tests are most efficient under standard regularity conditions, but they are highly non-robust even under small deviations…

Methodology · Statistics 2018-05-01 Ayanendranath Basu , Abhijit Mandal , Nirian Martin , Leandro Pardo

We construct examples of degree-two U- and V-statistics of $n$ i.i.d.~heavy-tailed random vectors in $\mathbb{R}^{d(n)}$, whose $\nu$-th moments exist for ${\nu > 2}$, and provide tight bounds on the error of approximating both statistics…

Statistics Theory · Mathematics 2024-06-19 Kevin Han Huang , Peter Orbanz

Due to the effort of a number of authors, the value c_u of the absolute constant factor in the uniform Berry--Esseen (BE) bound for sums of independent random variables has been gradually reduced to 0.4748 in the iid case and 0.5600 in the…

Probability · Mathematics 2013-05-10 Iosif Pinelis

We present simple to implement Wald-type statistics that deliver a general nonparametric inference theory for linear restrictions on varying coefficients in a range of regression models allowing for cross-sectional or spatial dependence. We…

Econometrics · Economics 2026-01-27 Abhimanyu Gupta , Xi Qu , Sorawoot Srisuma , Jiajun Zhang

Concentration inequalities for the sample mean, like those due to Bernstein, Hoeffding, and Bentkus, are valid for any sample size but overly conservative, yielding confidence intervals that are unnecessarily wide. The central limit theorem…

Probability · Mathematics 2025-12-23 Morgane Austern , Lester Mackey

Concentration inequalities form an essential toolkit in the study of high dimensional (HD) statistical methods. Most of the relevant statistics literature in this regard is based on sub-Gaussian or sub-exponential tail assumptions. In this…

Statistics Theory · Mathematics 2023-01-09 Arun Kumar Kuchibhotla , Abhishek Chakrabortty

We establish a general Berry-Esseen type bound which gives optimal bounds in many situations under suitable moment assumptions. By combining the general bound with Palm theory, we deduce a new error bound for assessing the accuracy of…

Probability · Mathematics 2020-09-01 Louis H. Y. Chen , Adrian Röllin , Aihua Xia

The Wald test statistic has been shown to diverge (Dufour et al, 2013, 2017) under some conditions. This note links the divergence to eigenvalues of a polynomial matrix and establishes the divergence rate.

Statistics Theory · Mathematics 2019-06-17 Jean-Marie Dufour , Eric Renault , Victoria Zinde-Walsh

Motivated by the application of saddlepoint approximations to resampling-based statistical tests, we prove that the Lugannani-Rice formula has vanishing relative error when applied to approximate conditional tail probabilities of averages…

Statistics Theory · Mathematics 2025-06-30 Ziang Niu , Jyotishka Ray Choudhury , Eugene Katsevich

This paper deals with the issue of testing hypothesis in symmetric and log-symmetric linear regression models in small and moderate-sized samples. We focus on four tests, namely the Wald, likelihood ratio, score, and gradient tests. These…

Methodology · Statistics 2016-02-03 Francisco M. C. Medeiros , Silvia L. P. Ferrari

We establish a finite-sample Berry-Esseen theorem for the entrywise limits of the eigenvectors for a broad collection of signal-plus-noise random matrix models under challenging weak signal regimes. The signal strength is characterized by a…

Statistics Theory · Mathematics 2022-03-08 Fangzheng Xie

This paper studies inference for the mean vector of a high-dimensional $U$-statistic. In the era of Big Data, the dimension $d$ of the $U$-statistic and the sample size $n$ of the observations tend to be both large, and the computation of…

Statistics Theory · Mathematics 2019-01-29 Xiaohui Chen , Kengo Kato

We propose an estimator for the singular vectors of high-dimensional low-rank matrices corrupted by additive subgaussian noise, where the noise matrix is allowed to have dependence within rows and heteroskedasticity between them. We prove…

Statistics Theory · Mathematics 2022-09-15 Joshua Agterberg , Zachary Lubberts , Carey Priebe

Determining whether an algorithmic decision-making system discriminates against a specific demographic typically involves comparing a single point estimate of a fairness metric against a predefined threshold. This practice is statistically…

Machine Learning · Computer Science 2026-03-20 Antonio Ferrara , Francesco Cozzi , Alan Perotti , André Panisson , Francesco Bonchi

An analogue of the Berry-Esseen inequality is proved for the speed of convergence of free additive convolutions of bounded probability measures. The obtained rate of convergence is of the order n^{-1/2}, the same as in the classical case.…

Probability · Mathematics 2007-09-03 Vladislav Kargin

We derive Berry-Esseen approximation bounds for general functionals of independent random variables, based on chaos expansions methods. Our results apply to $U$-statistics satisfying the weak assumption of decomposability in the Hoeffding…

Probability · Mathematics 2020-10-12 Nicolas Privault , Grzegorz Serafin

We study how eigenvectors of random regular graphs behave when projected onto fixed directions. For a random $d$-regular graph with $N$ vertices, where the degree $d$ grows slowly with $N$, we prove that these projections follow…

Probability · Mathematics 2025-07-22 Leonhard Nagel

It is shown that the absolute constant in the Berry--Esseen inequality for i.i.d. Bernoulli random variables is strictly less than the Esseen constant, if $1\le n\le 500000$, where $n$ is a number of summands. This result is got both with…

Probability · Mathematics 2018-10-24 Anatolii Zolotukhin , Sergei Nagaev , Vladimir Chebotarev

Randomly censored survival data are frequently encountered in applied sciences including biomedical or reliability applications and clinical trial analyses. Testing the significance of statistical hypotheses is crucial in such analyses to…

Methodology · Statistics 2019-01-08 Abhik Ghosh , Ayanendranath Basu , Leandro Pardo