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作者：Kowal, Daniel R.
作者单位：Rice University
摘要：Prediction is critical for decision-making under uncertainty and lends validity to statistical inference. With targeted prediction, the goal is to optimize predictions for specific decision tasks of interest, which we represent via functionals. Although classical decision analysis extracts predictions from a Bayesian model, these predictions are often difficult to interpret and slow to compute. Instead, we design a class of parameterized actions for Bayesian decision analysis that produce opti...
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作者：Li, Sai; Cai, T. Tony; Li, Hongzhe
作者单位：University of Pennsylvania; University of Pennsylvania
摘要：Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear mixed-effects models with high-dimensional fixed effects. The proposed method is applicable to general settings where the dimension of the random effects and the cluster sizes are possibly large. Regarding the fixed effects, we provide rate optimal estimators and valid inference procedures that do n...
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作者：Zammit-Mangion, Andrew; Ng, Tin Lok James; Vu, Quan; Filippone, Maurizio
作者单位：University of Wollongong; IMT - Institut Mines-Telecom; EURECOM
摘要：Spatial processes with nonstationary and anisotropic covariance structure are often used when modeling, analyzing, and predicting complex environmental phenomena. Such processes may often be expressed as ones that have stationary and isotropic covariance structure on a warped spatial domain. However, the warping function is generally difficult to fit and not constrained to be injective, often resulting in space-folding. Here, we propose modeling an injective warping function through a composit...
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作者：Deb, Nabarun; Saha, Sujayam; Guntuboyina, Adityanand; Sen, Bodhisattva
作者单位：Columbia University; Alphabet Inc.; Google Incorporated; University of California System; University of California Berkeley
摘要：In this article, we study a generalization of the two-groups model in the presence of covariates-a problem that has recently received much attention in the statistical literature due to its applicability in multiple hypotheses testing problems. The model we consider allows for infinite dimensional parameters and offers flexibility in modeling the dependence of the response on the covariates. We discuss the identifiability issues arising in this model and systematically study several estimation...
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作者：Cai, Tianxi; Liu, Molei; Xia, Yin
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Fudan University
摘要：Evidence-based decision making often relies on meta-analyzing multiple studies, which enables more precise estimation and investigation of generalizability. Integrative analysis of multiple heterogeneous studies is, however, highly challenging in the ultra high-dimensional setting. The challenge is even more pronounced when the individual-level data cannot be shared across studies, known as DataSHIELD contraint. Under sparse regression models that are assumed to be similar yet not identical ac...
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作者：Lyu, Ziyang; Welsh, A. H.
作者单位：University of Queensland; Australian National University
摘要：In this article we derive the asymptotic distribution of estimated best linear unbiased predictors (EBLUPs) of the random effects in a nested error regression model. Under very mild conditions which do not require the assumption of normality, we show that asymptotically the distribution of the EBLUPs as both the number of clusters and the cluster sizes diverge to infinity is the convolution of the true distribution of the random effects and a normal distribution. This result yields very simple...
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作者：Li, Quefeng; Li, Lexin
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of California System; University of California Berkeley
摘要：Multimodal data, where different types of data are collected from the same subjects, are fast emerging in a large variety of scientific applications. Factor analysis is commonly used in integrative analysis of multimodal data, and is particularly useful to overcome the curse of high dimensionality and high correlations. However, there is little work on statistical inference for factor analysis-based supervised modeling of multimodal data. In this article, we consider an integrative linear regr...
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作者：Schochet, Peter Z.; Pashley, Nicole E.; Miratrix, Luke W.; Kautz, Tim
作者单位：Mathematica; Rutgers University System; Rutgers University New Brunswick; Harvard University
摘要：This article develops design-based ratio estimators for clustered, blocked randomized controlled trials (RCTs), with an application to a federally funded, school-based RCT testing the effects of behavioral health interventions. We consider finite population weighted least-square estimators for average treatment effects (ATEs), allowing for general weighting schemes and covariates. We consider models with block-by-treatment status interactions as well as restricted models with block indicators ...
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作者：Zhang, Jingnan; He, Xin; Wang, Junhui
作者单位：City University of Hong Kong; Shanghai University of Finance & Economics
摘要：Community detection in network data aims at grouping similar nodes sharing certain characteristics together. Most existing methods focus on detecting communities in undirected networks, where similarity between nodes is measured by their node features and whether they are connected. In this article, we propose a novel method to conduct network embedding and community detection simultaneously in a directed network. The network embedding model introduces two sets of vectors to represent the out-...
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作者：McShane, Blakeley B.; Bockenholt, Ulf; Hansen, Karsten T.
作者单位：Northwestern University; University of California System; University of California San Diego
摘要：Over the last decade, large-scale replication projects across the biomedical and social sciences have reported relatively low replication rates. In these large-scale replication projects, replication has typically been evaluated based on a single replication study of some original study and dichotomously as successful or failed. However, evaluations of replicability that are based on a single study and are dichotomous are inadequate, and evaluations of replicability should instead be based on ...
