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The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known…

Machine Learning · Computer Science 2023-04-11 Shuai Li , Ziqi Chen , Hongtu Zhu , Christina Dan Wang , Wang Wen

In this paper we investigate the asymptotic distribution of likelihood ratio tests in models with several groups, when the number of groups converges with the dimension and sample size to infinity. We derive central limit theorems for the…

Statistics Theory · Mathematics 2019-07-17 Holger Dette , Nina Dörnemann

Kernel-weighted test statistics have been widely used in a variety of settings including non-stationary regression, inference on propensity score and panel data models. We develop the limit theory for a kernel-based specification test of a…

Econometrics · Economics 2023-05-30 Sid Kankanala , Victoria Zinde-Walsh

Symmetry plays a crucial role in quantum physics, dictating the behavior and dynamics of physical systems. In this paper, we develop a hypothesis-testing framework for quantum dynamics symmetry using a limited number of queries to the…

Quantum Physics · Physics 2025-04-01 Yu-Ao Chen , Chenghong Zhu , Keming He , Yingjian Liu , Xin Wang

Economic theory implies strong limitations on what types of consumption behavior are considered rational. Rationality implies that the Slutsky matrix, which captures the substitution effects of compensated price changes on demand for…

Econometrics · Economics 2026-02-11 Florian Gunsilius , Lonjezo Sithole

This article gives a synopsis on new developments in affine invariant tests for multivariate normality in an i.i.d.-setting, with special emphasis on asymptotic properties of several classes of weighted $L^2$-statistics. Since weighted…

Statistics Theory · Mathematics 2020-04-17 Bruno Ebner , Norbert Henze

Based on a generalized cosine measure between two symmetric matrices, we propose a general framework for one-sample and two-sample tests of covariance and correlation matrices. We also develop a set of associated permutation algorithms for…

Methodology · Statistics 2018-12-05 Longyang Wu , Chengguo Weng , Xu Wang , Kesheng Wang , Xuefeng Liu

Randomization is a common technique used in clinical trials to eliminate potential bias and confounders in a patient population. Equal allocation to treatment groups is the standard due to its optimal efficiency in many cases. However, in…

Applications · Statistics 2020-04-09 Thevaa Chandereng , Xiaodan Wei , Rick Chappell

Biometric recognition is used across a variety of applications from cyber security to border security. Recent research has focused on ensuring biometric performance (false negatives and false positives) is fair across demographic groups.…

Methodology · Statistics 2022-08-24 Michael Schuckers , Sandip Purnapatra , Kaniz Fatima , Daqing Hou , Stephanie Schuckers

Symmetric quantum states are fascinating objects. They correspond to multipartite systems that remain invariant under particle permutations. This symmetry is reflected in their compact mathematical characterisation but also in their unique…

Quantum Physics · Physics 2025-07-15 Carlo Marconi , Guillem Müller-Rigat , Jordi Romero-Pallejà , Jordi Tura , Anna Sanpera

This paper examines the problem of nonparametric testing for the no-effect of a random covariate (or predictor) on a functional response. This means testing whether the conditional expectation of the response given the covariate is almost…

Statistics Theory · Mathematics 2014-11-25 Valentin Patilea , Cesar Sanchez-Sellero , Matthieu Saumard

Quantifying the uncertainty of predictions is a core problem in modern statistics. Methods for predictive inference have been developed under a variety of assumptions, often -- for instance, in standard conformal prediction -- relying on…

Methodology · Statistics 2024-09-13 Edgar Dobriban , Mengxin Yu

This paper develops tests for inequality constraints of nonparametric regression functions. The test statistics involve a one-sided version of $L_p$-type functionals of kernel estimators $(1 \leq p < \infty)$. Drawing on the approach of…

Statistics Theory · Mathematics 2023-08-28 Sokbae Lee , Kyungchul Song , Yoon-Jae Whang

In this paper, we consider testing the homogeneity for proportions in independent binomial distributions especially when data are sparse for large number of groups. We provide broad aspects of our proposed tests such as theoretical studies,…

Statistics Theory · Mathematics 2017-12-14 Junyong Park

Switchback experiments--alternating treatment and control over time--are widely used when unit-level randomization is infeasible, outcomes are aggregated, or user interference is unavoidable. In practice, experimentation must support fast…

Methodology · Statistics 2026-02-27 Jizhou Liu , Liang Zhong

This work is about understanding the impact of invariance and equivariance on generalisation in supervised learning. We use the perspective afforded by an averaging operator to show that for any predictor that is not equivariant, there is…

Machine Learning · Computer Science 2025-01-08 Hayder Elesedy

The theory of plasma physics offers a number of nontrivial examples of partial differential equations, which can be successfully treated with symmetry methods. We propose three different examples which may illustrate the reciprocal…

Mathematical Physics · Physics 2008-04-24 Giampaolo Cicogna , Francesco Ceccherini , Francesco Pegoraro

We propose a new setting for testing properties of distributions while receiving samples from several distributions, but few samples per distribution. Given samples from $s$ distributions, $p_1, p_2, \ldots, p_s$, we design testers for the…

Data Structures and Algorithms · Computer Science 2019-11-19 Maryam Aliakbarpour , Sandeep Silwal

It is common to conduct causal inference in matched observational studies by proceeding as though treatment assignments within matched sets are assigned uniformly at random and using this distribution as the basis for inference. This…

Methodology · Statistics 2023-11-14 Samuel D. Pimentel , Yaxuan Huang

For a set of dependent random variables, without stationary or the strong mixing assumptions, we derive the asymptotic independence between their sums and maxima. Then we apply this result to high-dimensional testing problems, where we…

Methodology · Statistics 2022-05-12 Long Feng , Tiefeng Jiang , Xiaoyun Li , Binghui Liu
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