-
作者：Pavani, Jessica; Loschi, Rosangela H.; Quintana, Fernando A.
作者单位：University of Calgary; Universidade Federal de Minas Gerais; Pontificia Universidad Catolica de Chile
摘要：Time-dependent regionalization, or spatially restricted grouping, is a significant area of research focused on understanding the evolution of spatial clusters over time. In this study we adopt a probabilistic approach to regionalization, conceptualizing it as a random partition of geographic space at each time point, with the sequence of spatial partitions exhibiting time dependency. This methodology facilitates inference regarding the temporal dynamics of clusters. We employ a product partiti...
-
作者：Pavani, Jessica; Loschi, Rosangela H.; Quintana, Fernando A.
作者单位：University of Calgary; Universidade Federal de Minas Gerais; Pontificia Universidad Catolica de Chile
摘要：Time-dependent regionalization, or spatially restricted grouping, is a significant area of research focused on understanding the evolution of spatial clusters over time. In this study we adopt a probabilistic approach to regionalization, conceptualizing it as a random partition of geographic space at each time point, with the sequence of spatial partitions exhibiting time dependency. This methodology facilitates inference regarding the temporal dynamics of clusters. We employ a product partiti...
-
作者：Zens, Gregor; Bijak, Jakub
作者单位：International Institute for Applied Systems Analysis (IIASA); University of Oxford; University of Oxford
摘要：Motivated by the challenge of analyzing the dynamics of weekly sea border crossings in the Mediterranean (2015-2025) and the English Channel (2018-2025), we develop a Bayesian dynamic framework for modeling heteroskedastic count time series. Building on theoretical considerations and empirical stylized facts, our approach utilizes a Poisson random walk model that allows for heavy-tailed innovations or stochastic volatility dynamics, while incorporating an explicit mechanism to separate structu...
-
作者：Zhou, Yuhang; Qiu, Peihua
作者单位：State University System of Florida; University of Florida
摘要：Our society is under constant threat from outbreaks of various infectious diseases, such as COVID-19, Zika, and others. The recent COVID-19 pandemic has claimed millions of lives and caused devastating disruption to our daily routines. Prompt detection of outbreaks and effective disease surveillance are critical yet challenging, due to the complex spatiotemporal dynamics of infectious disease spread. Existing analytical tools often rely on restrictive assumptions, such as data independence and...
-
作者：Li, Yijun; Choi, Ki Sueng; Dunlop, Boadie W.; Craighead, W. Edward; Mayberg, Helen S.; Garmire, Lana; Guo, Ying; Kang, Jian
作者单位：University of Michigan System; University of Michigan; Icahn School of Medicine at Mount Sinai; Emory University; University of Michigan System; University of Michigan; Emory University; Rollins School Public Health
摘要：Brain connectivity analysis is crucial for understanding brain structure and neurological function, shedding light on the mechanisms of mental illness. To study the association between individual brain connectivity networks and the clinical characteristics, we develop BSNMani: a Bayesian scalar-on-network regression model with manifold learning. BSNMani comprises two components: the network manifold learning model for brain connectivity networks, which extracts shared connectivity structures a...
-
作者：Deighton, Jared; Mackey, Wyatt; Schizas, Ioannis; Boothe, David l.; Maroulas, Vasileios
作者单位：University of Tennessee System; University of Tennessee Knoxville; United States Department of Defense; US Army Research, Development & Engineering Command (RDECOM); US Army Research Laboratory (ARL)
摘要：Understanding how neural populations efficiently encode stimuli is a fundamental challenge in computational neuroscience. Existing rate-based inforinto population-level representations, while the role of correlation in neural coding remains a subject of considerable debate. To address this, we introduce novel, correlation-aware information-theoretic measures that quantify the encoding efficiency of multiple neurons, including the joint stimulus information rate for neuron pairs and the spectra...
-
作者：Lee, Hane; Sobel, Michael E.
作者单位：Columbia University
摘要：The extent to which the American public is politically polarized is of great interest in the lay and academic communities. To study opinion polarization, political scientists and public opinion researchers examine the distribution of respondents on survey items, using visual comparison of histograms and/or measures such as variances and bimodality coefficients. We prove these measures fail to align with prevailing conceptualizations of polarization put forth in the literature. To remedy this s...
-
作者：Luo, Yingcheng; Wang, Shiyu; Shen, Chong; Li, Yichao; Qin, Zhaohui S.; Deng, Ke
作者单位：Tsinghua University; Emory University; Rollins School Public Health
摘要：Revealing the spatial organization of biomolecules and characterizing their spatial distribution in cells and tissues have long been recognized as important problems in biomedical research. With rapid advances in DNA sequencing technologies in recent years, creative sequencing-based experimental assays, for example, Hi-C and DNA microscopy, have been invented to reveal the spatial properties of large-scale biomolecules in a high-throughput and high-resolution manner. A typical experiment based...
-
作者：He, Yuheng; Zou, Changliang; Zhao, Yi
作者单位：Nankai University; Indiana University System; Indiana University Bloomington
摘要：In the high-dimensional landscape, addressing the challenges of covariance regression with high-dimensional predictors has posed difficulties for conventional methodologies. This paper addresses these hurdles by presenting a novel approach for high-dimensional inference with covariance matrix outcomes. The proposed methodology is demonstrated through its application in identifying patterns of brain co-activation observed in functional magnetic resonance imaging (fMRI) experiments and in reveal...
-
作者：Stevenson, Ben c.; Smit, Elizabeth; Setyawan, Edy
作者单位：University of Auckland
摘要：An understanding of the body size of individuals and the relationships between different dimensions is critical for monitoring the status and the health of a wildlife population. Morphometric data have traditionally been collected by physically handling and measuring individual animals, but recent technological advancements allow researchers to deploy sophisticated but affordable instruments, like drones and camera traps, to take photos of individual animals from which morphometric measurement...
