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作者：Hoff, Peter
作者单位：Duke University
摘要：This article develops p-values for evaluating means of normal populations that make use of indirect or prior information. A p-value of this type is based on a biased frequentist hypothesis test that has optimal average power with respect to a probability distribution that encodes indirect information about the mean parameter, resulting in a smaller p-value if the indirect information is accurate. In a variety of multiparameter settings, we show how to adaptively estimate the indirect informati...
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作者：Betancourt, Brenda; Zanella, Giacomo; Steorts, Rebecca C.
作者单位：State University System of Florida; University of Florida; Bocconi University; Duke University
摘要：Traditional Bayesian random partition models assume that the size of each cluster grows linearly with the number of data points. While this is appealing for some applications, this assumption is not appropriate for other tasks such as entity resolution (ER), modeling of sparse networks, and DNA sequencing tasks. Such applications require models that yield clusters whose sizes grow sublinearly with the total number of data points-the microclustering property. Motivated by these issues, we propo...
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作者：Cressie, Noel
作者单位：University of Wollongong
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作者：Bonvini, Matteo; Kennedy, Edward H.
作者单位：Carnegie Mellon University
摘要：In observational studies, identification of ATEs is generally achieved by assuming that the correct set of confounders has been measured and properly included in the relevant models. Because this assumption is both strong and untestable, a sensitivity analysis should be performed. Common approaches include modeling the bias directly or varying the propensity scores to probe the effects of a potential unmeasured confounder. In this article, we take a novel approach whereby the sensitivity param...
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作者：Liu, Xiao; Yeo, Kyongmin; Lu, Siyuan
作者单位：University of Arkansas System; University of Arkansas Fayetteville; International Business Machines (IBM); IBM USA
摘要：This article proposes a physical-statistical modeling approach for spatio-temporal data arising from a class of stochastic convection-diffusion processes. Such processes are widely found in scientific and engineering applications where fundamental physics imposes critical constraints on how data can be modeled and how models should be interpreted. The idea of spectrum decomposition is employed to approximate a physical spatio-temporal process by the linear combination of spatial basis function...
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作者：Ray, Kolyan; Szabo, Botond
作者单位：Imperial College London; Vrije Universiteit Amsterdam
摘要：We study a mean-field spike and slab variational Bayes (VB) approximation to Bayesian model selection priors in sparse high-dimensional linear regression. Under compatibility conditions on the design matrix, oracle inequalities are derived for the mean-field VB approximation, implying that it converges to the sparse truth at the optimal rate and gives optimal prediction of the response vector. The empirical performance of our algorithm is studied, showing that it works comparably well as other...
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作者：Banerjee, Sudipto
作者单位：University of California System; University of California Los Angeles
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作者：Zhang, Likun; Shaby, Benjamin A.; Wadsworth, Jennifer L.
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Colorado State University System; Colorado State University Fort Collins; Lancaster University
摘要：Flexible spatial models that allow transitions between tail dependence classes have recently appeared in the literature. However, inference for these models is computationally prohibitive, even in moderate dimensions, due to the necessity of repeatedly evaluating the multivariate Gaussian distribution function. In this work, we attempt to achieve truly high-dimensional inference for extremes of spatial processes, while retaining the desirable flexibility in the tail dependence structure, by mo...
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作者：Zhang, Zhengwu; Wang, Xiao; Kong, Linglong; Zhu, Hongtu
作者单位：University of North Carolina; University of North Carolina Chapel Hill; Purdue University System; Purdue University; University of Alberta; University of North Carolina; University of North Carolina Chapel Hill
摘要：This article develops a novel spatial quantile function-on-scalar regression model, which studies the conditional spatial distribution of a high-dimensional functional response given scalar predictors. With the strength of both quantile regression and copula modeling, we are able to explicitly characterize the conditional distribution of the functional or image response on the whole spatial domain. Our method provides a comprehensive understanding of the effect of scalar covariates on function...
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作者：Tian, Qinglong; Meng, Fanqi; Nordman, Daniel J.; Meeker, William Q.
作者单位：Iowa State University
摘要：This article describes prediction methods for the number of future events from a population of units associated with an on-going time-to-event process. Examples include the prediction of warranty returns and the prediction of the number of future product failures that could cause serious threats to property or life. Important decisions such as whether a product recall should be mandated are often based on such predictions. Data, generally right-censored (and sometimes left truncated and right-...
