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To combat the HIV/AIDS pandemic effectively, targeted interventions among certain key populations play a critical role. Examples of such key populations include sex workers, people who inject drugs, and men who have sex with men. While…

Applications · Statistics 2021-07-14 Jacob Parsons , Xiaoyue Niu , Le Bao

Preserving biodiversity and ecosystem stability is a challenge that can be pursued through modern statistical mechanics modeling. Here we introduce a variational maximum entropy-based algorithm to evaluate the entropy in a minimal ecosystem…

Biological Physics · Physics 2018-10-17 Mattia Miotto , Lorenzo Monacelli

Assessing variability according to distinct factors in data is a fundamental technique of statistics. The method commonly regarded to as analysis of variance (ANOVA) is, however, typically confined to the case where all levels of a factor…

Methodology · Statistics 2013-03-15 Steven Geinitz , Reinhard Furrer

Term enrichment analysis facilitates biological interpretation by assigning to experimentally/computationally obtained data annotation associated with terms from controlled vocabularies. This process usually involves obtaining statistical…

Quantitative Methods · Quantitative Biology 2011-10-25 Aleksandar Stojmirović , Yi-Kuo Yu

Reliable mortality estimates at the subnational level are essential in the study of health inequalities within a country. One of the difficulties in producing such estimates is the presence of small populations, where the stochastic…

Applications · Statistics 2017-12-05 Monica Alexander , Emilio Zagheni , Magali Barbieri

The measurement of the efficiency of an event selection is always an important part of the analysis of experimental data. The statistical techniques which are needed to determine the efficiency and its uncertainty are reviewed. Frequentist…

Data Analysis, Statistics and Probability · Physics 2012-08-28 Diego Casadei

Numerous statistics have been proposed for the measure of offensive ability in major league baseball. While some of these measures may offer moderate predictive power in certain situations, it is unclear which simple offensive metrics are…

Applications · Statistics 2021-07-21 Blakeley B. McShane , Alexander Braunstein , James Piette , Shane T. Jensen

Biogeographical regions (geographically distinct assemblages of species and communities) constitute a cornerstone for ecology, biogeography, evolution and conservation biology. Species turnover measures are often used to quantify…

Quantitative Methods · Quantitative Biology 2015-08-19 Daril A. Vilhena , Alexandre Antonelli

Categories such as animal or furniture are acquired at an early age and play an important role in processing, organizing, and communicating world knowledge. Categories exist across cultures: they allow to efficiently represent the…

Computation and Language · Computer Science 2019-02-26 Lea Frermann , Mirella Lapata

Model-based approaches for (bio)process systems often suffer from incomplete knowledge of the underlying physical, chemical, or biological laws. Universal differential equations, which embed neural networks within differential equations,…

Machine Learning · Statistics 2026-05-20 Arno Strouwen

For many taxonomic groups, online biodiversity portals used by naturalists and citizen scientists constitute the primary source of distributional information. Over the last decade, site-occupancy models have been advanced as a promising…

This work investigates how biodiversity is affected in a cyclic spatial May-Leonard model with hierarchical and non-hierarchical rules. Here we propose a generalization of the traditional rock-paper-scissors model by considering highly…

Populations and Evolution · Quantitative Biology 2025-05-08 D. Bazeia , M. J. B. Ferreira , B. F. de Oliveira , W. A. dos Santos

Processes in ocean physics, air-sea interaction and ocean biogeochemistry span enormous ranges in spatial and temporal scales, that is, from molecular to planetary and from seconds to millennia. Identifying and implementing sustainable…

Methodology · Statistics 2013-12-23 Christopher K. Wikle , Ralph F. Milliff , Radu Herbei , William B. Leeds

Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or…

Physics and Society · Physics 2016-01-25 Dániel Czégel , Gergely Palla

Estimates of uncertainty or variance in experimental means are central to physics. This is especially the case for `world averages' of fundamental physical parameters in particle physics, which aggregate results from a number of experiments…

High Energy Physics - Experiment · Physics 2023-10-13 Fintan Costello , Paul Watts

Understanding how and why certain communities bear a disproportionate burden of disease is challenging due to the scarcity of data on these communities. Surveys provide a useful avenue for accessing hard-to-reach populations, as many…

Methodology · Statistics 2023-07-27 Stephanie M. Wu , Briana Joy K. Stephenson

Many countries measure poverty based only on income or consumption. However, there is a growing awareness of measuring poverty through multiple dimensions that captures a more reasonable status of poverty. Estimating poverty measure(s) for…

Methodology · Statistics 2025-10-13 Soumojit Das , Dilshanie Deepawansa , Partha Lahiri

Accurate estimates of microbial species abundances are needed to advance our understanding of the role that microbiomes play in human and environmental health. However, artificially constructed microbiomes demonstrate that intuitive…

Methodology · Statistics 2025-03-17 David S Clausen , Amy D Willis

Differential analysis is a routine procedure in the statistical analysis toolbox across many applied fields, including quantitative proteomics, the main illustration of the present paper. The state-of-the-art limma approach uses a…

Methodology · Statistics 2025-12-12 Marie Chion , Arthur Leroy

This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning problem where the model assumes a shared sparsity structure across different tasks. We derive a…

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