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作者：Hoeltgebaum, Henrique; Adams, Niall; Lau, F. Din-Houn
作者单位：Imperial College London
摘要：Structural health monitoring (SHM) often involves instrumenting structures with distributed sensor networks. These networks typically provide high frequency data describing the spatiotemporal behaviour of the assets. A main objective of SHM is to reason about changes in structures' behaviour using sensor data. We construct a streaming anomaly detection method for data from a railway bridge instrumented with a fibre-optic sensor network. The data exhibits trend over time, which may be partially...
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作者：Pfister, Niklas; Williams, Evan G.; Peters, Jonas; Aebersold, Ruedi; Buehlmann, Peter
作者单位：University of Copenhagen; University of Luxembourg; Swiss Federal Institutes of Technology Domain; ETH Zurich; Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：We consider regression in which one predicts a response Y with a set of predictors X across different experiments or environments. This is a common setup in many data-driven scientific fields, and we argue that statistical inference can benefit from an analysis that takes into account the distributional changes across environments. In particular, it is useful to distinguish between stable and unstable predictors, that is, predictors which have a fixed or a changing functional dependence on the...
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作者：Li, Cai; Zhang, Heping
作者单位：Yale University
摘要：Human intelligence is usually measured by well-established psychometric tests through a series of problem solving. The recorded cognitive scores are continuous but usually heavy-tailed with potential outliers and violating the normality assumption. Meanwhile, magnetic resonance imaging (MRI) provides an unparalleled opportunity to study brain structures and cognitive ability. Motivated by association studies between MRI images and human intelligence, we propose a tensor quantile regression mod...
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作者：Hadj-Amar, Beniamino; Finkenstadt, Barbel; Fiecas, Mark; Huckstepp, Robert
作者单位：University of Warwick; University of Minnesota System; University of Minnesota Twin Cities; University of Warwick
摘要：We propose to model time-varying periodic and oscillatory processes by means of a hidden Markov model where the states are defined through the spectral properties of a periodic regime. The number of states is unknown along with the relevant periodicities, the role and number of which may vary across states. We address this inference problem by a Bayesian nonparametric hiddenMarkov model, assuming a sticky hierarchical Dirichlet process for the switching dynamics between different states while ...
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作者：Risk, Benjamin B.; Gaynanova, Irina
作者单位：Emory University; Texas A&M University System; Texas A&M University College Station
摘要：As advances in technology allow the acquisition of complementary information, it is increasingly common for scientific studies to collect multiple datasets. Large-scale neuroimaging studies often include multiple modalities (e.g., task functional MRI, resting-state fMRI, diffusion MRI, and/or structural MRI) with the aim to understand the relationships between datasets. In this study, we seek to understand whether regions of the brain activated in a working memory task relate to resting-state ...
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作者：Yu, Menggang; Kuang, Chensheng; Huling, Jared D.; Smith, Maureen
作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; University of Minnesota System; University of Minnesota Twin Cities; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
摘要：Thirty-day rehospitalization rate is a well-studied and important measure reflecting the overall performance of health systems. Recently, transitional care (TC) programs have been initiated to reduce avoidable rehospitalizations. These programs typically ask nurses to follow-up with patients after the hospitalization to manage issues and reduce the risk of rehospitalizations during health care transitions. As rehospitalization is a complex process that depends on many factors, it is unlikely t...
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作者：Hepler, Staci A.; Waller, Lance A.; Kline, David M.
作者单位：Wake Forest University; Emory University; University System of Ohio; Ohio State University
摘要：Ohio is one of the states most impacted by the opioid epidemic and experienced the second highest age-adjusted fatal drug overdose rate in 2017. Initially it was believed prescription opioids were driving the opioid crisis in Ohio. However, as the epidemic evolved, opioid overdose deaths due to fentanyl have drastically increased. In this work we develop a Bayesian multivariate spatiotemporal model for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids. The lo...
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作者：West, Brady T.; Little, Roderick J.; Andridge, Rebecca R.; Boonstra, Philip S.; Ware, Erin B.; Pandit, Anita; Alvarado-Leiton, Fernanda
作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University System of Ohio; Ohio State University; University of Michigan System; University of Michigan
摘要：Selection bias is a serious potential problem for inference about relationships of scientific interest based on samples without well-defined probability sampling mechanisms. Motivated by the potential for selection bias in: (a) estimated relationships of polygenic scores (PGSs) with phenotypes in genetic studies of volunteers and (b) estimated differences in subgroup means in surveys of smartphone users, we derive novel measures of selection bias for estimates of the coefficients in linear and...
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作者：Starling, Jennifer E.; Murray, Jared S.; Lohr, Patricia A.; Aiken, Abigail R. A.; Carvalho, Carlos M.; Scott, James G.
作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
摘要：We introduce Targeted Smooth Bayesian Causal Forests (tsBCF), a non-parametric Bayesian approach for estimating heterogeneous treatment effects which vary smoothly over a single covariate in the observational data setting. The tsBCF method induces smoothness by parameterizing terminal tree nodes with smooth functions and allows for separate regularization of treatment effects vs. prognostic effect of control covariates. Smoothing parameters for prognostic and treatment effects can be chosen to...
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作者：Wang, Lin; Elmstedt, Jake; Wong, Weng Kee; Xu, Hongquan
作者单位：George Washington University; University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
摘要：The dramatic growth of big datasets presents a new challenge to data storage and analysis. Data reduction, or subsampling, that extracts useful information from datasets is a crucial step in big-data analysis. We propose an orthogonal subsampling (OSS) approach for big data with a focus on linear regression models. The approach is inspired by the fact that an orthogonal array of two levels provides the best experimental design for linear regression models in the sense that it minimizes the ave...
