The Annals of Applied Statistics

最新文章

• PROBABILISTIC CONTRASTIVE DIMENSION REDUCTION FOR CASE-CONTROL STUDY DATA AI翻译
  作者：Li, Didong; Jones, Andrew; Engelhardt, Barbara
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine; Princeton University; University of California System; University of California San Francisco; The J David Gladstone Institutes
  摘要：Case-control experiments are essential to the scientific method, as they allow researchers to test biological hypotheses by looking for differences in outcome between cases and controls. It is then of interest to characterize variation that is enriched in a foreground (case) dataset relative to a background (control) dataset. For example, in a genomics context, the goal is to identify low-dimensional transcriptional structure unique to patients with certain disease (cases) vs. those without th...
• FUNCTIONAL CONCURRENT REGRESSION WITH COMPOSITIONAL COVARIATES AND ITS APPLICATION TO THE TIME-VARYING EFFECT OF CAUSES OF DEATH ON HUMAN LONGEVITY AI翻译
  作者：Depaoli, Giovanni; Stefanucci, Marco; Mazzuco, Stefano
  作者单位：University of Padua; University of Rome Tor Vergata
  摘要：Multivariate functional data that are cross-sectionally compositional data are attracting increasing interest in the statistical modeling literature, a major example being trajectories over time of compositions derived from causespecific mortality rates. In this work we develop a novel functional concurrent regression model in which independent variables are functional compositions. This allows us to investigate the relationship over time between life expectancy at birth and compositions deriv...
• A BEHAVIORAL APPROACH TO REPEATED BAYESIAN SECURITY GAMES AI翻译
  作者：Caballero, William; Cooley, Jake; Banks, David; Jenkins, Phillip
  作者单位：United States Department of Defense; United States Air Force; Duke University; Air Force Institute of Technology (AFIT)
  摘要：The prevalence of security threats to organizational defense demands models that support real -world policymaking. Security games are a potent tool in this regard; however, although canonical models effectively allocate limited resources, they generally do not consider adaptive, boundedly rational adversaries. Empirical findings suggest this characterization describes real -world human behavior, so the development of decision -support frameworks against such adversaries is a critical need. We ...
• A PARTIALLY FUNCTIONAL LINEAR REGRESSION FRAMEWORK FOR INTEGRATING GENETIC, IMAGING, AND CLINICAL DATA AI翻译
  作者：Li, Ting; Yu, Yang; Marron, J. S.; Zhu, Hongtu
  作者单位：Shanghai University of Finance & Economics; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
  摘要：This paper is motivated by the joint analysis of genetic, imaging, and clinical (GIC) data collected in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We propose a partially functional linear regression (PFLR) framework to map high -dimensional GIC-related pathways for Alzheimer's disease (AD). We develop a joint model selection and estimation procedure by embedding imaging data in the reproducing kernel Hilbert space and imposing the t0 penalty for the coefficients of genetic v...
• A LATENT MIXTURE MODEL FOR HETEROGENEOUS CAUSAL MECHANISMS IN MENDELIAN RANDOMIZATION AI翻译
  作者：Long, Daniel; Zho, Qingyuan; Chen, Yang
  作者单位：University of Michigan System; University of Michigan; University of Cambridge
  摘要：Mendelian randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for causal inference. Existing MR methods usually assume most genetic variants are valid instrumental variables that identify a common causal effect. There is a general lack of awareness that this effect homogeneity assumption can be violated when there are multiple causal pathways involved, even if all the instrumental variables are valid. In this article we intr...
• A CONTINUOUS MULTIPLE HYPOTHESIS TESTING FRAMEWORK FOR OPTIMAL EXOPLANET DETECTION AI翻译
  作者：Hara, Nathan C.; De Poyferre, Thibault; Delisle, Jean-Baptiste; Hoffmann, Marc
  作者单位：University of California System; University of California Berkeley; Universite PSL; Universite Paris-Dauphine
  摘要：When searching for exoplanets, one wants to count how many planets orbit a given star, and to determine what their characteristics are. If the estimated planet characteristics are too far from those of a planet truly present, this should be considered as a false detection. This setting is a particular instance of a general one: aiming to retrieve parametric components in a dataset corrupted by nuisance signals, with a certain accuracy on their parameters. We exhibit a detection criterion minim...
• ESTIMATING FIBER ORIENTATION DISTRIBUTION WITH APPLICATION TO STUDY BRAIN LATERALIZATION USING HCP D-MRI DATA AI翻译
  作者：Hwang, Seungyong; Lee, Thomas C. M.; Paul, Debashis; Peng, Jie
  作者单位：University of California System; University of California Davis
  摘要：Diffusion -weighted magnetic resonance imaging (D-MRI) is an in vivo and noninvasive imaging technology for characterizing tissue microstructure in biological samples. A major application of D-MRI is for white matter fiber tract reconstruction in brains. It begins by estimating the water molecule movements (serving as proxies for fiber directions) in the brain voxels and then combines the results to form fiber tracts. The voxel-level fiber direction information can be modeled by a fiber orient...
• DISTRIBUTED PROPORTIONAL LIKELIHOOD RATIO MODEL WITH APPLICATION TO DATA INTEGRATION ACROSS CLINICAL SITES AI翻译
  作者：Luo, Chongliang; Duan, Rui; Edmondson, Mackenzie; Shi, Jiasheng; Maltenfort, Mitchell; Morris, Jeffrey S.; Forrest, Christopher B.; Hubbard, Rebecca; Chen, Yong
  作者单位：Washington University (WUSTL); Harvard University; Harvard T.H. Chan School of Public Health; University of Pennsylvania; University of Pennsylvania; Pennsylvania Medicine; Childrens Hospital of Philadelphia
  摘要：Real -world evidence synthesis through integration of data from distributed research networks has gained increasing attention in recent years. Due to privacy concerns and restrictions of sharing patient -level data, distributed algorithms that do not require sharing patient level information are in great need for facilitating multisite collaborations. On the other hand, data collected at multiple sites often come from diverse populations, and there exists a substantial amount of heterogeneity ...
• SENSITIVITY ANALYSIS OF WIND ENERGY RESOURCES WITH BAYESIAN NON-GAUSSIAN AND NONSTATIONARY FUNCTIONAL ANOVA AI翻译
  作者：Zhang, Jiachen; Crippa, Paola; Genton, Marc G.; Castruccio, Stefano
  作者单位：University of Notre Dame; University of Notre Dame; King Abdullah University of Science & Technology
  摘要：The transition from nonrenewable to renewable energies represents a global societal challenge, and developing a sustainable energy portfolio is an especially daunting task for developing countries where little to no information is available regarding the abundance of renewable resources such as wind. Weather model simulations are key to obtain such information when observational data are scarce and sparse over a country as large and geographically diverse as Saudi Arabia. However, output from ...
• ACCOUNTING FOR SEASONALITY IN EXTREME SEA-LEVEL ESTIMATION AI翻译
  作者：D'Arcy, Eleanor; Tawn, Jonathan A.; Joly, Amelie; Sifnioti, Dafni E.
  作者单位：Lancaster University
  摘要：Reliable estimates of sea-level return-levels are crucial for coastal flooding risk assessments and for coastal flood defence design. We describe a novel method for estimating extreme sea-levels that is the first to capture seasonality, interannual variations and longer term changes. We use a joint probabilities method, with skew-surge and peak-tide as two sea-level components. The tidal regime is predictable, but skew-surges are stochastic. We present a statistical model for skew-surges, wher...