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作者：Jewell, Nicholas P.
作者单位：University of London; London School of Hygiene & Tropical Medicine
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作者：Das, Kiranmoy; Ghosh, Pulak; Daniels, Michael J.
作者单位：Indian Statistical Institute; Indian Statistical Institute Kolkata; Indian Institute of Management (IIM System); Indian Institute of Management Bangalore; State University System of Florida; University of Florida
摘要：As the population of the older individuals continues to grow, it is important to study the relationship among the variables measuring financial health and physical health of the older individuals to better understand the demand for healthcare, and health insurance. We propose a semiparametric approach to jointly model these variables. We use data from the Health and Retirement Study which includes a set of correlated longitudinal variables measuring financial and physical health. In particular...
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作者：Awan, Jordan; Slavkovic, Aleksandra
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Differential privacy (DP) provides a framework for provable privacy protection against arbitrary adversaries, while allowing the release of summary statistics and synthetic data. We address the problem of releasing a noisy real-valued statistic vectorT, a function of sensitive data under DP, via the class ofK-norm mechanisms with the goal of minimizing the noise added to achieve privacy. First, we introduce thesensitivity space of T, which extends the concepts of sensitivity polytope and sensi...
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作者：Mao, Xueyu; Sarkar, Purnamrita; Chakrabarti, Deepayan
作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin
摘要：We consider the problem of estimating community memberships of nodes in a network, where every node is associated with a vector determining its degree of membership in each community. Existing provably consistent algorithms often require strong assumptions about the population, are computationally expensive, and only provide an overall error bound for the whole community membership matrix. This article provides uniform rates of convergence for the inferred community membership vector ofeachnod...
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作者：Shi, Chengchun; Song, Rui; Lu, Wenbin; Li, Runze
作者单位：University of London; London School Economics & Political Science; North Carolina State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：In this article, we develop a new estimation and valid inference method for single or low-dimensional regression coefficients in high-dimensional generalized linear models. The number of the predictors is allowed to grow exponentially fast with respect to the sample size. The proposed estimator is computed by solving a score function. We recursively conduct model selection to reduce the dimensionality from high to a moderate scale and construct the score equation based on the selected variable...
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作者：Lawrence, Earl; Vander Wiel, Scott
作者单位：United States Department of Energy (DOE); Los Alamos National Laboratory
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作者：Williams, Jonathan P.
作者单位：North Carolina State University
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作者：Sansom, Philip G.; Stephenson, David B.; Bracegirdle, Thomas J.
作者单位：University of Exeter; UK Research & Innovation (UKRI); Natural Environment Research Council (NERC); NERC British Antarctic Survey
摘要：Numerical climate models are used to project future climate change due to both anthropogenic and natural causes. Differences between projections from different climate models are a major source of uncertainty about future climate. Emergent relationships shared by multiple climate models have the potential to constrain our uncertainty when combined with historical observations. We combine projections from 13 climate models with observational data to quantify the impact of emergent relationships...
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作者：Kivaranovic, Danijel; Leeb, Hannes
作者单位：University of Vienna
摘要：Valid inference after model selection is currently a very active area of research. The polyhedral method, introduced in an article by Lee et al., allows for valid inference after model selection if the model selection event can be described by polyhedral constraints. In that reference, the method is exemplified by constructing two valid confidence intervals when the Lasso estimator is used to select a model. We here study the length of these intervals. For one of these confidence intervals, wh...
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作者：de Micheaux, Pierre Lafaye; Mozharovskyi, Pavlo; Vimond, Myriam
作者单位：University of New South Wales Sydney; IMT - Institut Mines-Telecom; Institut Polytechnique de Paris; Telecom Paris; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Humanities & Social Sciences (INSHS); Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
摘要：In 1975, John W. Tukey defined statistical data depth as a function that determines the centrality of an arbitrary point with respect to a data cloud or to a probability measure. During the last decades, this seminal idea of data depth evolved into a powerful tool proving to be useful in various fields of science. Recently, extending the notion of data depth to the functional setting attracted a lot of attention among theoretical and applied statisticians. We go further and suggest a notion of...
