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作者：Zhang, Lyuyuan; Qian, Guoqi; Das, Sourav
作者单位：University of Melbourne; James Cook University
摘要：Tropical cyclones (TC) are significant indicators of evolving climate dynamics. Two primary responses of interest are the cyclone frequency and intensity. In this paper we propose a novel integrated modelling framework for simultaneous modelling of TC frequency across several meteorological regions within Australasia. The key methodological insight is to model the second-order properties of multiple integer-valued time series in frequency domain, instead of parametric time domain models. We ta...
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作者：Miralles, Ophelia; Davison, Anthony c.
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：Despite its importance for insurance, there is almost no literature on statistical hail damage modeling. Statistical models for hailstorms exist, though they are generally not open-source, but no study appears to have developed a stochastic hail impact function. In this paper we use hail-related insurance claim data to build a Gaussian line process with extreme marks in order to model both the geographical footprint of a hailstorm and the damage to buildings that hailstones can cause. We build...
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作者：Parker, Matthew R. P.; Cao, Jiguo; Cowen, Laura l. E.; Elliott, Lloyd T.; Ma, Junling
作者单位：Simon Fraser University; University of Victoria
摘要：Even with daily case counts, the true scope of the COVID-19 pandemic in Canada is unknown due to undetected cases. We develop a novel multivalued multivariate time series in the framework of Bayesian hidden Markov modelling techniques. We apply our multisite model to estimate the pandemic scope using publicly available disease count data including detected cases, recoveries among detected cases, and total deaths. These counts are used to estimate the case detection probability, the infection f...
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作者：Upton, Elizabeth; Carvalho, Luis
作者单位：Williams College; Boston University
摘要：Analyses of occurrences of residential burglary in urban areas have shown that crime rates are not spatially homogeneous: rates vary across the network of city streets, resulting in some areas being far more susceptible to crime than others. The explanation for why a certain segment of the city experiences high crime may be different than why a neighboring area experiences high crime. Motivated by the importance of understanding spatial patterns such as these, we consider a statistical model o...
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作者：Shook-Sa, Bonnie E.; Hudgens, Michael G.; Knittel, Andrea K.; Edmonds, Andrew; Ramirez, Catalina; Cole, Stephen R.; Cohen, Mardge; Adedimeji, Adebola; Taylor, Tonya; Michel, Katherine G.; Kovacs, Andrea; Cohen, Jennifer; Donohue, Jessica; Foster, Antonina; Fischl, Margaret A.; Long, Dustin; Adimora, Adaora A.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; John H Stroger Junior Hospital Cook County; Montefiore Medical Center; Albert Einstein College of Medicine; Yeshiva University; State University of New York (SUNY) System; SUNY Downstate Health Sciences University; Georgetown University; University of Southern California; University of California System; University of California San Francisco; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Emory University; University of Miami; University of Alabama System; University of Alabama Birmingham
摘要：Causal inference methods can be applied to estimate the effect of a point exposure or treatment on an outcome of interest using data from observational studies. For example, in the Women's Interagency HIV Study, it is of interest to understand the effects of incarceration on the number of sexual partners and the number of cigarettes smoked after incarceration. In settings like this where the outcome is a count, the estimand is often the causal mean ratio, that is, the ratio of the counterfactu...
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作者：Woody, Jonathan; Zhao, Zhicong; Lund, Robert; Wu, Tung-Lung
作者单位：Mississippi State University; University of California System; University of California Santa Cruz
摘要：This study develops methods to detect anomalous transactions linked with fraud in food stamp purchases through order statistics methods. The methods detect clusters in the order statistics of the transaction amounts that merit further scrutiny. Our techniques use scan statistics to determine when an excessive number of transactions occur (cluster), which is historically linked to fraud. A scoring paradigm is constructed that ranks the degree in which detected clusters and individual transactio...
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作者：Pitkin, James; Manolopoulou, Ioanna; Ross, Gordon
作者单位：Alan Turing Institute; University of London; University College London; University of Edinburgh
摘要：The field of retail analytics has been transformed by the availability of rich data, which can be used to perform tasks such as demand forecasting and inventory management. However, one task which has proved more challenging is the forecasting of demand for products which exhibit very few sales. The sparsity of the resulting data limits the degree to which traditional analytics can be deployed. To combat this, we represent sales data as a structured sparse multivariate point process, which all...
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作者：Lin, Zikai; Si, Yajuan; Kang, Jian
作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
摘要：Image -on -scalar regression has been a popular approach to modeling the association between brain activities and scalar characteristics in neuroimaging research. The associations could be heterogeneous across individuals in the population, as indicated by recent large-scale neuroimaging studies, for example, the Adolescent Brain Cognitive Development (ABCD) Study. The ABCD data can inform our understanding of heterogeneous associations and how to leverage the heterogeneity and tailor interven...
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作者：Chakraborty, Moumita; Baladandayuthapani, Veerabhadran; Bhadra, Anindya; Ha, Min jin
作者单位：University of Texas System; University of Texas Medical Branch Galveston; University of Michigan System; University of Michigan; Purdue University System; Purdue University; Yonsei University
摘要：Integrative analysis of multilevel pharmacogenomic data for modeling dependencies across various biological domains is crucial for developing genomic-testing based treatments. Chain graphs characterize conditional dependence structures of such multilevel data where variables are naturally partitioned into multiple ordered layers, consisting of both directed and undirected edges. Existing literature mostly focus on Gaussian chain graphs, which are ill-suited for nonnormal distributions with hea...
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作者：Zhang, Maoyu; Cai, Biao; Dai, Wenlin; Kong, Dehan; Zhao, Hongyu; Zhang, Jingfei
作者单位：Emory University; City University of Hong Kong; Renmin University of China; University of Toronto; Yale University
摘要：Dynamic networks have been increasingly used to characterize brain connectivity that varies during resting and task states. In such characterizations a connectivity network is typically measured at each time point for a subject over a common set of nodes representing brain regions, together with rich subject-level information. A common approach to analyzing such data is an edge-based method that models the connectivity between each pair of nodes separately. However, such approach may have limi...
