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High-dimensional mixed data as a combination of both continuous and ordinal variables are widely seen in many research areas such as genomic studies and survey data analysis. Estimating the underlying correlation among mixed data is hence…

Methodology · Statistics 2018-09-18 Xiaoyun Quan , James G. Booth , Martin T. Wells

The infant microbiome undergoes rapid changes in composition over time and is associated with long-term risks of conditions such as immune strength, allergy, asthma, and other health outcomes. Modeling the associations between exposures or…

Methodology · Statistics 2026-03-31 Brody Erlandson , Ander Wilson , Matthew D. Koslovsky

This paper studies the data-driven balanced truncation (BT) method for second-order systems based on the measurements in the frequency domain. The basic idea is to approximate Gramians used the numerical quadrature rules, and establish the…

Numerical Analysis · Mathematics 2025-06-05 Xiaolong Wang , Xuerong Yang , Xiaoli Wang , Bo Song

The Wilcoxon Signed Rank test is typically called upon when testing whether a symmetric distribution has a specified centre and the Gaussianity is in question. As with all insurance policies it comes with a cost, even if small, in terms of…

Statistics Theory · Mathematics 2017-08-03 Jonathan Rosenblatt , Yoav Benjamini

High-dimensional compositional data arise naturally in many applications such as metagenomic data analysis. The observed data lie in a high-dimensional simplex, and conventional statistical methods often fail to produce sensible results due…

Methodology · Statistics 2016-01-19 Yuanpei Cao , Wei Lin , Hongzhe Li

There has been a growing acknowledgement of the involvement of the gut microbiome - the collection of microbes that reside in our gut - in regulating our mood and behaviour. This phenomenon is referred to as the microbiome-gut-brain axis.…

Genomics · Quantitative Biology 2023-12-11 Thomaz F. S. Bastiaanssen , Thomas P. Quinn , Amy Loughman

We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect covariate information, which has the potential to significantly boost performance. However,…

Machine Learning · Statistics 2026-05-05 Gyumin Lee , Shubhanshu Shekhar , Ilmun Kim

We study global inference for regression coefficients in high-dimensional linear models under potentially heavy-tailed errors. While sum-type tests are powerful for dense alternatives and max-type tests excel for sparse alternatives,…

Methodology · Statistics 2026-03-17 Ping Zhao , Liangliang Yuan

We propose a novel hierarchical model for multitask bipartite ranking. The proposed approach combines a matrix-variate Gaussian process with a generative model for task-wise bipartite ranking. In addition, we employ a novel trace…

Machine Learning · Computer Science 2013-02-12 Oluwasanmi Koyejo , Cheng Lee , Joydeep Ghosh

The workhorse model for zero-truncated count data (y = 1, 2, ...) is the zero-truncated negative binomial (ZTNB) model. We find it should seldom be used. Instead, we recommend the one-inflated zero-truncated negative binomial (OIZTNB) model…

Econometrics · Economics 2025-03-24 Ryan T. Godwin

In this paper, we investigate right-truncated count data models incorporating cavariates into the parameters. A regression method is proposed to model right-truncated count data exibiting high heterogeneity. The study encompasses the…

Methodology · Statistics 2025-03-11 Babagnidé François Koladjo , Ricardo Anderson Donte , Epiphane Sodjinou

In nonadaptive group testing, the main research objective is to design an efficient algorithm to identify a set of up to $t$ positive elements among $n$ samples with as few tests as possible. Disjunct matrices and separable matrices are two…

Combinatorics · Mathematics 2021-10-15 Bingchen Qian , Xin Wang , Gennian Ge

Statistics in ranked lists is important in analyzing molecular biology measurement data, such as ChIP-seq, which yields ranked lists of genomic sequences. State of the art methods study fixed motifs in ranked lists. More flexible models…

Quantitative Methods · Quantitative Biology 2013-07-31 Limor Leibovich , Zohar Yakhini

The Mann-Whitney-Wilcoxon rank sum test (MWWRST) is a widely used method for comparing two treatment groups in randomized control trials, particularly when dealing with highly skewed data. However, when applied to observational study data,…

The log-rank test and the Cox proportional hazards model are commonly used to compare time-to-event data in clinical trials, as they are most powerful under proportional hazards. But there is a loss of power if this assumption is violated,…

Methodology · Statistics 2024-02-14 Jonas Brugger , Tim Friede , Florian Klinglmüller , Martin Posch , Robin Ristl , Franz König

We propose a novel kernel-based two-sample test that leverages the spectral decomposition of the maximum mean discrepancy (MMD) statistic to identify and utilize well-estimated directional components in reproducing kernel Hilbert space…

Methodology · Statistics 2025-08-21 Rui Cui , Yuhao Li , Xiaojun Song

The stochastic block model is a popular tool for detecting community structures in network data. Detecting the difference between two community structures is an important issue for stochastic block models. However, the two-sample test has…

Methodology · Statistics 2022-12-21 Kang Fu , Jianwei Hu , Seydou Keita , Hao Liu

The use of patient-level information from previous studies, registries, and other external datasets can support the analysis of single-arm and randomized controlled trials to evaluate and test experimental treatments. However, the…

Methodology · Statistics 2025-10-23 Gopal Kotecha , Daniel E. Schwartz , Steffen Ventz , Lorenzo Trippa

We consider multivariate two-sample tests of means, where the location shift between the two populations is expected to be related to a known graph structure. An important application of such tests is the detection of differentially…

Quantitative Methods · Quantitative Biology 2014-05-16 Laurent Jacob , Pierre Neuvial , Sandrine Dudoit

Models such as the zero-inflated and zero-altered Poisson and zero-truncated binomial are well-established in modern regression analysis. We propose a super model that jointly and maximally unifies alteration, inflation, truncation and…

Methodology · Statistics 2022-08-30 Thomas W. Yee , Chenchen Ma