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We establish the validity of bootstrap methods for empirical likelihood (EL) inference under the density ratio model (DRM). In particular, we prove that the bootstrap maximum EL estimators share the same limiting distribution as their population counterparts, both at the parameter level and for distribution functionals...
Statistics TheoryFOS: MathematicsStatistics Theory (math.ST)mathematics
Traditional statistical inference in cluster randomized trials typically invokes the asymptotic theory that requires the number of clusters to approach infinity. In this article, we propose an alternative conformal causal inference framework for analyzing cluster randomized trials that achieves the target inferential g...
Methodology (stat.ME)FOS: Computer and information sciencesmedical and health sciencesclinical medicine
Wang, Shouxia · Cao, Jiguo · Liu, Hua · You, Jinhong · y 1 más
It is of great interest to test the equality of the means in two samples of functional data. Past research has predominantly concentrated on low-dimensional functional data, a focus that may not hold up in high-dimensional scenarios. In this article, we propose a novel two-sample test for the mean functions of high-dim...
Methodology (stat.ME)FOS: Computer and information sciencesMethodology
Two-sample hypothesis testing is a fundamental problem with various applications, which faces new challenges in the high-dimensional context. To mitigate the issue of the curse of dimensionality, high-dimensional data are typically assumed to lie on a low-dimensional manifold. To incorporate geometric information in th...
Methodology (stat.ME)FOS: Computer and information sciences62G10, 62G20Methodology
Feature selection and importance estimation in a model-agnostic setting is an ongoing challenge of significant interest. Wrapper methods are commonly used because they are typically model-agnostic. In this paper, we develop a general comparison framework for model-agnostic feature selection methods based on relative ef...
Machine LearningMethodology (stat.ME)FOS: Computer and information sciencesMethodology
In this thesis detailed quantum oscillation (QO) studies have been performed on two different van der Waals layered, square-net material systems, i.e., the Dirac nodal line (DNL) semimetals ZrSiS, HfSiS, and ZrSiSe, all members of the ZrSiS material family, and CeTe3, a member of the rare-earth tritellurides (RETe3). A...
Correlationsphysical sciencessquare-net materialsHigh magnetic fields
We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle large state spaces and support transparent decision-making, we model the Q-function using a nonlinear function class with a sparse additive structure. We derive high-probabi...
Machine LearningFOS: Computer and information sciencesStatistics TheoryFOS: Mathematics
Data privacy is important in the AI era, and differential privacy (DP) is one of the golden solutions. However, DP is typically applicable only if data have a bounded underlying distribution. We address this limitation by leveraging second-moment information from a small amount of public data. We propose Public-moment-...
Machine LearningMethodology (stat.ME)FOS: Computer and information sciencesPrimary 62F30, secondary 62J05, 62J12, 62G20, 68P27
Regression models for compositional data are common in several areas of knowledge. As in other classes of regression models, it is desirable to perform diagnostic analysis in these models using residuals that are approximately standard normally distributed. However, for regression models for compositional data, there h...
Methodology (stat.ME)FOS: Computer and information sciencesComputationMethodology
This dataset is connected to a thesis. In this thesis we propose the diamagnetic steering of polymersome nanomotors as a solution for directional motion. Diamagnetic steering is the biocompatible alternative for ferro- or paramagnetic steering, which relies on the incorporation of ferro/paramagnetic materials in the po...
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