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作者：Qiu, Hongxiang; Carone, Marco; Sadikova, Ekaterina; Petukhova, Maria; Kessler, Ronald C.; Luedtke, Alex
作者单位：University of Washington; University of Washington Seattle; Harvard University; Harvard Medical School; University of Washington; University of Washington Seattle
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作者：Sarkar, Abhra; Pati, Debdeep; Mallick, Bani K.; Carroll, Raymond J.
作者单位：University of Texas System; University of Texas Austin; Texas A&M University System; Texas A&M University College Station; University of Technology Sydney
摘要：Estimating the marginal and joint densities of the long-term average intakes of different dietary components is an important problem in nutritional epidemiology. Since these variables cannot be directly measured, data are usually collected in the form of 24-hr recalls of the intakes, which show marked patterns of conditional heteroscedasticity. Significantly compounding the challenges, the recalls for episodically consumed dietary components also include exact zeros. The problem of estimating ...
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作者：Hu, Jianwei; Zhang, Jingfei; Qin, Hong; Yan, Ting; Zhu, Ji
作者单位：Central China Normal University; University of Miami; Zhongnan University of Economics & Law; University of Michigan System; University of Michigan
摘要：The stochastic block model is widely used for detecting community structures in network data. How to test the goodness of fit of the model is one of the fundamental problems and has gained growing interests in recent years. In this article, we propose a novel goodness-of-fit test based on the maximum entry of the centered and rescaled adjacency matrix for the stochastic block model. One noticeable advantage of the proposed test is that the number of communities can be allowed to grow linearly ...
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作者：Guo, Xinzhou; He, Xuming
作者单位：University of Michigan System; University of Michigan
摘要：When existing clinical trial data suggest a promising subgroup, we must address the question of how good the selected subgroup really is. The usual statistical inference applied to the selected subgroup, assuming that the subgroup is chosen independent of the data, may lead to an overly optimistic evaluation of the selected subgroup. In this article, we address the issue of selection bias and develop a de-biasing bootstrap inference procedure for the best selected subgroup effect. The proposed...
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作者：Sun, Qiang; Zhang, Heping
作者单位：University of Toronto; Yale University
摘要：Analysis of high-dimensional data has received considerable and increasing attention in statistics. In practice, we may not be interested in every variable that is observed. Instead, often some of the variables are of particular interest, and the remaining variables are nuisance. To this end, we propose the nuisance penalized regression which does not penalize the parameters of interest. When the coherence between interest parameters and nuisance parameters is negligible, we show that resultin...
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作者：Kellogg, Maxwell; Mogstad, Magne; Pouliot, Guillaume A.; Torgovitsky, Alexander
作者单位：National Bureau of Economic Research; University of Chicago; National Bureau of Economic Research; University of Chicago
摘要：The synthetic control (SC) method is widely used in comparative case studies to adjust for differences in pretreatment characteristics. SC limits extrapolation bias at the potential expense of interpolation bias, whereas traditional matching estimators have the opposite properties. This complementarity motives us to propose a matching and synthetic control (or MASC) estimator as a model averaging estimator that combines the standard SC and matching estimators. We show how to use a rolling-orig...
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作者：Quick, Corbin; Dey, Rounak; Lin, Xihong
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University
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作者：Li, Zhigang; Tian, Lu; O'Malley, A. James; Karagas, Margaret R.; Hoen, Anne G.; Christensen, Brock C.; Madan, Juliette C.; Wu, Quran; Gharaibeh, Raad Z.; Jobin, Christian; Li, Hongzhe
作者单位：State University System of Florida; University of Florida; Stanford University; Dartmouth College; Dartmouth College; State University System of Florida; University of Florida; University of Pennsylvania
摘要：The target of inference in microbiome analyses is usually relative abundance (RA) because RA in a sample (e.g., stool) can be considered as an approximation of RA in an entire ecosystem (e.g., gut). However, inference on RA suffers from the fact that RA are calculated by dividing absolute abundances (AAs) over the common denominator (CD), the summation of all AA (i.e., library size). Because of that, perturbation in one taxon will result in a change in the CD and thus cause false changes in RA...
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作者：Avella-Medina, Marco
作者单位：Columbia University
摘要：Differential privacy is a cryptographically motivated approach to privacy that has become a very active field of research over the last decade in theoretical computer science and machine learning. In this paradigm, one assumes there is a trusted curator who holds the data of individuals in a database and the goal of privacy is to simultaneously protect individual data while allowing the release of global characteristics of the database. In this setting, we introduce a general framework for par...
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作者：Chen, Haoyu; Lu, Wenbin; Song, Rui
作者单位：North Carolina State University
摘要：Online decision making problem requires us to make a sequence of decisions based on incremental information. Common solutions often need to learn a reward model of different actions given the contextual information and then maximize the long-term reward. It is meaningful to know if the posited model is reasonable and how the model performs in the asymptotic sense. We study this problem under the setup of the contextual bandit framework with a linear reward model. The epsilon-greedy policy is a...
