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作者：Fasano, Augusto; Denti, Francesco
作者单位：University of Turin; University of Padua
摘要：The computation of multivariate Gaussian cumulative distribution functions is a key step in many statistical procedures, often representing a crucial computational bottleneck. Over the past few decades, efficient algorithms have been proposed to address this problem, mainly using Monte Carlo solutions. This work highlights a connection between the multivariate Gaussian cumulative distribution function and the marginal likelihood of a tailored dual Bayesian probit model. Consequently, any metho...
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作者：Liang, B.; Zhang, L.; Janson, L.
作者单位：Harvard University
摘要：A partial conjunction hypothesis test combines information across a set of base hypotheses to determine whether some subset is nonnull. Partial conjunction hypothesis tests arise in a diverse array of fields, but standard partial conjunction hypothesis testing methods can be highly conservative, leading to low power especially in low-signal settings commonly encountered in applications. In this paper, we introduce the conditional partial conjunction hypothesis test, a new method for testing a ...
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作者：Wu, Yinxiang; Kang, Hyunseung; Ye, Ting
作者单位：University of Washington; University of Washington Seattle; University of Wisconsin System; University of Wisconsin Madison
摘要：Multivariable Mendelian randomization uses genetic variants as instrumental variables to infer the direct effects of multiple exposures on an outcome. However, unlike univariable Mendelian randomization, multivariable Mendelian randomization often faces greater challenges with many weak instruments, which can lead to bias not necessarily toward zero and inflation of Type-I errors. In this work, we introduce a new asymptotic regime that allows exposures to have varying degrees of instrument str...
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作者：Heng, J.; De Bortoli, V; Doucet, A.; Thornton, J.
作者单位：ESSEC Business School; Universite PSL; Ecole Normale Superieure (ENS); University of Oxford
摘要：We consider the problem of simulating diffusion bridges, which are diffusion processes that are conditioned to initialize and terminate at two given states. The simulation of diffusion bridges has applications in diverse scientific fields and plays a crucial role in the statistical inference of discretely observed diffusions. This is known to be a challenging problem that has received much attention in the last two decades. This article contributes to this rich body of literature by presenting...
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作者：Xu, Jiazhen; Wood, Andrew T. A.; Zou, Tao
作者单位：Australian National University
摘要：Functional data analysis offers a diverse toolkit of statistical methods tailored to analysing samples of real-valued random functions. Recently, samples of time-varying random objects, such as time-varying networks, have been increasingly encountered in data analysis. These data structures represent elements within general metric spaces that lack local or global linear structures, rendering traditional functional data analysis methods inapplicable. Moreover, the existing methodology for time-...
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作者：Li, Jinming; Xu, Gongjun; Zhu, Ji
作者单位：University of Michigan System; University of Michigan
摘要：Factor analysis is a statistical tool widely used in many disciplines, such as psychology, economics and sociology. As observations linked by networks become increasingly common, incorporating network structures into factor analysis is an important problem that remains open. This article focuses on high-dimensional factor analysis involving network-connected observations, and we propose a generalized factor model with latent factors that account for both the network structure and the dependenc...
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作者：Stolf, F.; Dunson, D. B.
作者单位：Duke University
摘要：Joint species distribution models are popular in ecology for modelling covariate effects on species occurrence, while characterizing cross-species dependence. Data consist of multivariate binary indicators of the occurrences of different species in each sample, along with sample-specific covariates. A key problem is that current models implicitly assume that the list of species under consideration is predefined and finite, while for highly diverse groups of organisms, it is impossible to antic...
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作者：Gui, Lin; Jiang, Yuchao; Wang, Jingshu
作者单位：University of Chicago; Texas A&M University System; Texas A&M University College Station
摘要：Combining dependent $ p $-values poses a long-standing challenge in statistical inference, particularly when aggregating findings from multiple methods to enhance signal detection. Recently, $ p $-value combination tests based on regularly-varying-tailed distributions, such as the Cauchy combination test and harmonic mean $ p $-value, have attracted attention for their robustness to unknown dependence. This paper provides a theoretical and empirical evaluation of these methods under an asympto...
