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作者：Zhao, Jiwei; Ma, Yanyuan
作者单位：University of Wisconsin System; University of Wisconsin Madison; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：We consider the estimation problem in a regression setting where the outcome variable is subject to nonignorable missingness and identifiability is ensured by the shadow variable approach. We propose a versatile estimation procedure where modeling of missingness mechanism is completely bypassed. We show that our estimator is easy to implement and we derive the asymptotic theory of the proposed estimator. We also investigate some alternative estimators under different scenarios. Comprehensive s...
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作者：Zhao, Sihai Dave; Biscarri, William
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; Capital One Financial Corporation
摘要：Problems involving the simultaneous estimation of multiple parameters arise in many areas of theoretical and applied statistics. A canonical example is the estimation of a vector of normal means. Frequently, structural information about relationships between the parameters of interest is available. For example, in a gene expression denoising problem, genes with similar functions may have similar expression levels. Despite its importance, structural information has not been well-studied in the ...
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作者：Duarte, Belmiro P. M.; Atkinson, Anthony C.; Granjo, Jose F. O.; Oliveira, Nuno M. C.
作者单位：Instituto Politecnico de Coimbra (IPC); Universidade de Coimbra; Universidade de Coimbra; University of London; London School Economics & Political Science
摘要：Explicit models representing the response variables as functions of the control variables are standard in virtually all scientific fields. For these models, there is a vast literature on the optimal design of experiments (ODoE) to provide good estimates of the parameters with the use of minimal resources. Contrarily, the ODoE for implicit models is more complex and has not been systematically addressed. Nevertheless, there are practical examples where the models relating the response variables...
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作者：She, Yiyuan; Wang, Zhifeng; Shen, Jiahui
作者单位：State University System of Florida; Florida State University
摘要：Outliers widely occur in big-data applications and may severely affect statistical estimation and inference. In this article, a framework of outlier-resistant estimation is introduced to robustify an arbitrarily given loss function. It has a close connection to the method of trimming and includes explicit outlyingness parameters for all samples, which in turn facilitates computation, theory, and parameter tuning. To tackle the issues of nonconvexity and nonsmoothness, we develop scalable algor...
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作者：Li, Ting; Li, Tengfei; Zhu, Zhongyi; 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; Fudan University; University of North Carolina; University of North Carolina Chapel Hill
摘要：Many modern large-scale longitudinal neuroimaging studies, such as the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, have collected/are collecting asynchronous scalar and functional variables that are measured at distinct time points. The analyses of temporally asynchronous functional and scalar variables pose major technical challenges to many existing statistical approaches. We propose a class of generalized functional partial-linear varying-coefficient models to appropriately de...
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作者：Solea, Eftychia; Li, Bing
作者单位：University of Cyprus; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
摘要：We introduce a statistical graphical model for multivariate functional data, which are common in medical applications such as EEG and fMRI. Recently published functional graphical models rely on the multivariate Gaussian process assumption, but we relax it by introducing the functional copula Gaussian graphical model (FCGGM). This model removes the marginal Gaussian assumption but retains the simplicity of the Gaussian dependence structure, which is particularly attractive for large data. We d...
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作者：Man, Albert Xingyi; Culpepper, Steven Andrew
作者单位：University of Illinois System; University of Illinois Urbana-Champaign
摘要：Exploratory factor analysis is a dimension-reduction technique commonly used in psychology, finance, genomics, neuroscience, and economics. Advances in computational power have opened the door for fully Bayesian treatments of factor analysis. One open problem is enforcing rotational identifability of the latent factor loadings, as the loadings are not identified from the likelihood without further restrictions. Nonidentifability of the loadings can cause posterior multimodality, which can prod...
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作者：Fan, Jianqing; Liao, Yuan
作者单位：Princeton University; Rutgers University System; Rutgers University New Brunswick
摘要：Estimations and applications of factor models often rely on the crucial condition that the number of latent factors is consistently estimated, which in turn also requires that factors be relatively strong, data are stationary and weakly serially dependent, and the sample size be fairly large, although in practical applications, one or several of these conditions may fail. In these cases, it is difficult to analyze the eigenvectors of the data matrix. To address this issue, we propose simple es...
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作者：Khan, Kori; Calder, Catherine A.
作者单位：University System of Ohio; Ohio State University; University of Texas System; University of Texas Austin
摘要：The issue of spatial confounding between the spatial random effect and the fixed effects in regression analyses has been identified as a concern in the statistical literature. Multiple authors have offered perspectives and potential solutions. In this article, for the areal spatial data setting, we show that many of the methods designed to alleviate spatial confounding can be viewed as special cases of a general class of models. We refer to this class as restricted spatial regression (RSR) mod...
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作者：Gares, Valerie; Omer, Jeremy
作者单位：Universite de Rennes; Institut National des Sciences Appliquees de Rennes; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
摘要：When databases are constructed from heterogeneous sources, it is not unusual that different encodings are used for the same outcome. In such case, it is necessary to recode the outcome variable before merging two databases. The method proposed for the recoding is an application of optimal transportation where we search for a bijective mapping between the distributions of such variable in two databases. In this article, we build upon the work by Gares et al., where they transport the distributi...
