Journal of the American Statistical Association

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• Testing and Modeling Dependencies Between a Network and Nodal Attributes AI翻译
  作者：Fosdick, Bailey K.; Hoff, Peter D.
  作者单位：Colorado State University System; Colorado State University Fort Collins; University of Washington; University of Washington Seattle
  摘要：Network analysis is often focused on characterizing the dependencies between network relations and node-level attributes. Potential relationships are typically explored by modeling the network as a function of the nodal attributes or by modeling the attributes as a function of the network. These methods require specification of the exact nature of the association between the network and attributes, reduce the network data to a small number of summary statistics, and are unable to provide predi...
• Unifying Amplitude and Phase Analysis: A Compositional Data Approach to Functional Multivariate Mixed-Effects Modeling of Mandarin Chinese AI翻译
  作者：Hadjipantelis, P. Z.; Aston, J. A. D.; Mueller, H. G.; Evans, J. P.
  作者单位：University of Warwick; University of Warwick; University of Cambridge; University of California System; University of California Davis; Academia Sinica - Taiwan
  摘要：Mandarin Chinese is characterized by being a tonal language; the pitch (or F-0) of its utterances carries considerable linguistic information. However, speech samples from different individuals are subject to changes in amplitude and phase, which must be accounted for in any analysis that attempts to provide a linguistically meaningful description of the language. A joint model for amplitude, phase, and duration is presented, which combines elements from functional data analysis, compositional...
• A Unifying Model for Capture-Recapture and Distance Sampling Surveys of Wildlife Populations AI翻译
  作者：Borchers, D. L.; Stevenson, B. C.; Kidney, D.; Thomas, L.; Marques, T. A.
  作者单位：University of St Andrews
  摘要：A fundamental problem in wildlife ecology and management is estimation of population size or density. The two dominant methods in this area are capture-recapture (CR) and distance sampling (DS), each with its own largely separate literature. We develop a class of models that synthesizes them. It accommodates a spectrum of models ranging from nonspatial CR models (with no information on animal locations) through to DS and mark-recapture distance sampling (MRDS) models, in which animal locations...
• Simulating and Analyzing Order Book Data: The Queue-Reactive Model AI翻译
  作者：Huang, Weibing; Lehalle, Charles-Albert; Rosenbaum, Mathieu
  作者单位：Sorbonne Universite
  摘要：Through the analysis of a dataset of ultra high frequency order book updates, we introduce a model which accommodates the empirical properties of the full order book together with the stylized facts of lower frequency financial data. To do so, we split the time interval of interest into periods in which a well chosen reference price, typically the midprice, remains constant. Within these periods, we view the limit order book as a Markov queuing system. Indeed, we assume that the intensities of...
• Bayesian Inference of Multiple Gaussian Graphical Models AI翻译
  作者：Peterson, Christine; Stingo, Francesco C.; Vannucci, Marina
  作者单位：Stanford University; Rice University; University of Texas System; UTMD Anderson Cancer Center
  摘要：In this article, we propose a Bayesian approach to inference on multiple Gaussian graphical models. Specifically, we address the problem of inferring multiple undirected networks in situations where some of the networks may be unrelated, while others share common features. We link the estimation of the graph structures via a Markov random field (MRF) prior, which encourages common edges. We learn which sample groups have a shared graph structure by placing a spike-and-slab prior on the paramet...
• A Spatio-Temporal Point Process Model for Ambulance Demand AI翻译
  作者：Zhou, Zhengyi; Matteson, David S.; Woodard, Dawn B.; Henderson, Shane G.; Micheas, Athanasios C.
  作者单位：Cornell University; Cornell University; Cornell University; University of Missouri System; University of Missouri Columbia
  摘要：Ambulance demand estimation at fine time and location scales is critical for fleet management and dynamic deployment. We are motivated by the problem of estimating the spatial distribution of ambulance demand in Toronto, Canada, as it changes over discrete 2 hr intervals. This large-scale dataset is sparse at the desired temporal resolutions and exhibits location-specific serial dependence, daily, and weekly seasonality. We address these challenges by introducing a novel characterization of ti...
• Variable-Domain Functional Regression for Modeling ICU Data AI翻译
  作者：Gellar, Jonathan E.; Colantuoni, Elizabeth; Needham, Dale M.; Crainiceanu, Ciprian M.
  作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins Medicine
  摘要：We introduce a class of scalar-on-function regression models with subject-specific functional predictor domains. The fundamental idea is to consider a bivariate functional parameter that depends both on the functional argument and on the width of the functional predictor domain. Both parametric and nonparametric models are introduced to fit the functional coefficient. The nonparametric model is theoretically and practically invariant to functional support transformation, or support registratio...
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models AI翻译
  作者：Fan, Jianqing; Ma, Yunbei; Dai, Wei
  作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Princeton University; Southwestern University of Finance & Economics - China
  摘要：The varying coefficient model is an important class of nonparametric statistical model, which allows us to examine how the effects of covariates vary with exposure variables. When the number of covariates is large, the issue of variable selection arises. In this article, we propose and investigate marginal nonparametric screening methods to screen variables in sparse ultra-high-dimensional varying coefficient models. The proposed nonparametric independence screening (NIS) selects variables by ...
• Identifying Genetic Variants for Addiction via Propensity Score Adjusted Generalized Kendall's Tau AI翻译
  作者：Jiang, Yuan; Li, Ni; Zhang, Heping
  作者单位：Oregon State University; Hainan Normal University; Yale University; Yale University; Sun Yat Sen University
  摘要：Identifying replicable genetic variants for addiction has been extremely challenging. Besides the common difficulties with genome-wide association studies (GWAS), environmental factors are known to be critical to addiction, and comorbidity is widely observed. Despite the importance of environmental factors and comorbidity for addiction study, few GWAS analyses adequately considered them due to the limitations of the existing statistical methods. Although parametric methods have been developed ...
• Multivariate Analysis of Longitudinal Ordinal Data With Mixed Effects Models, With Application to Clinical Outcomes in Osteoarthritis AI翻译
  作者：Laffont, Celine Marielle; Vandemeulebroecke, Marc; Concordet, Didier
  作者单位：INRAE; Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Universite de Toulouse; Ecole Nationale Veterinaire de Toulouse; Universite Toulouse III - Paul Sabatier; Universite Federale Toulouse Midi-Pyrenees (ComUE); Institut National Polytechnique de Toulouse; Novartis
  摘要：Our objective was to evaluate the efficacy of robenacoxib in osteoarthritic dogs using four ordinal responses measured repeatedly over time. We propose a multivariate probit mixed effects model to describe the joint evolution of endpoints and to evidence the intrinsic correlations between responses that are not due to treatment effect. Maximum likelihood computation is intractable within reasonable time frames. We therefore use a pairwise modeling approach in combination with a stochastic EM a...