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作者：Xu, Yuhang; Li, Yehua; Nettleton, Dan
作者单位：University of Nebraska System; University of Nebraska Lincoln; University of California System; University of California Riverside; Iowa State University
摘要：In a plant science Root Image Study, the process of seedling roots bending in response to gravity is recorded using digital cameras, and the bending rates are modeled as functional plant phenotype data. The functional phenotypes are collected from seeds representing a large variety of genotypes and have a three-level nested hierarchical structure, with seeds nested in groups nested in genotypes. The seeds are imaged on different days of the lunar cycle, and an important scientific question is ...
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作者：Bugni, Federico A.; Canay, Ivan A.; Shaikh, Azeem M.
作者单位：Duke University; Northwestern University; University of Chicago
摘要：This article studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so as to achieve balance within each stratum. Our main requirement is that the randomization scheme assigns treatment status within each stratum so that the fraction of units being assigned to treatment w...
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作者：Crane, Harry; Dempsey, Walter
作者单位：Rutgers University System; Rutgers University New Brunswick; University of Michigan System; University of Michigan
摘要：Many modern network datasets arise from processes of interactions in a population, such as phone calls, email exchanges, co-authorships, and professional collaborations. In such interaction networks, the edges comprise the fundamental statistical units, making a framework for edge-labeled networks more appropriate for statistical analysis. In this context, we initiate the study of edge exchangeable network models and explore its basic statistical properties. Several theoretical and practical f...
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作者：Wang, Chao; Chan, Kung-Sik
作者单位：University of Iowa
摘要：Maximum likelihood estimation of a censored autoregressive model with exogenous variables (CARX) requires computing the conditional likelihood of blocks of data of variable dimensions. As the random block dimension generally increases with the censoring rate, maximum likelihood estimation becomes quickly numerically intractable with increasing censoring. We introduce a new estimation approach using the complete-incomplete data framework with the complete data comprising the observations were t...
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作者：Battiston, Marco; Favaro, Stefano; Teh, Yee Whye
作者单位：Bocconi University; University of Turin; Collegio Carlo Alberto; University of Oxford
摘要：Let (P-1, ..., P-J) denote J populations of animals from distinct regions. A priori, it is unknown which species are present in each region and what are their corresponding frequencies. Species are shared among populations and each species can be present in more than one region with its frequency varying across populations. In this article, we consider the problem of sequentially sampling these populations to observe the greatest number of different species. We adopt a Bayesian nonparametric a...
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作者：Genton, Marc G.; Jeong, Jaehong
作者单位：King Abdullah University of Science & Technology
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作者：Luedtke, Alexander R.; van der Laan, Mark J.
作者单位：University of California System; University of California Berkeley
摘要：Suppose one has a collection of parameters indexed by a (possibly infinite dimensional) set. Given data generated from some distribution, the objective is to estimate the maximal parameter in this collection evaluated at the distribution that generated the data. This estimation problem is typically nonregular when the maximizing parameter is nonunique, and as a result standard asymptotic techniques generally fail in this case. We present a technique for developing parametric-rate confidence in...
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作者：Parker, Albert E.; Pitts, Betsey; Lorenz, Lindsey; Stewart, Philip S.
作者单位：Montana State University System; Montana State University Bozeman; Montana State University System; Montana State University Bozeman; Montana State University System; Montana State University Bozeman
摘要：Three-dimensional confocal scanning laser microscope images offer dramatic visualizations of living biofilms before and after interventions. Here, we use confocal microscopy to study the effect of a treatment over time that causes a biofilm to swell and contract due to osmotic pressure changes. From these data (the video is provided in the supplementary materials), our goal is to reconstruct biofilm surfaces, to estimate the effect of the treatment on the biofilm's volume, and to quantify the ...
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作者：Philtron, Daisy; Lyu, Yafei; Li, Qunhua; Ghosh, Debashis
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Colorado School of Public Health; University of Colorado System; University of Colorado Anschutz Medical Campus
摘要：The identification of reproducible signals from the results of replicate high-throughput experiments is an important part of modern biological research. Often little is known about the dependence structure and the marginal distribution of the data, motivating the development of a nonparametric approach to assess reproducibility. The procedure, which we call the maximum rank reproducibility (MaRR) procedure, uses a maximum rank statistic to parse reproducible signals from noise without making a...
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作者：Sarkar, Abhra; Pati, Debdeep; Chakraborty, Antik; Mallick, Bani K.; Carroll, Raymond J.
作者单位：Duke University; University of Texas System; University of Texas Austin; State University System of Florida; Florida State University; Texas A&M University System; Texas A&M University College Station; University of Technology Sydney
摘要：We consider the problem of multivariate density deconvolution when interest lies in estimating the distribution of a vector valued random variable X but precise measurements on X are not available, observations being contaminated by measurement errors U. The existing sparse literature on the problem assumes the density of the measurement errors to be completely known. We propose robust Bayesian semiparametric multivariate deconvolution approaches when the measurement error density of U is not ...
