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作者：Tenzer, Yaniv; Mandel, Micha; Zuk, Or
作者单位：Hebrew University of Jerusalem; Weizmann Institute of Science
摘要：Testing for dependence between pairs of random variables is a fundamental problem in statistics. In some applications, data are subject to selection bias that can create spurious dependence. An important example is truncation models, in which observed pairs are restricted to a specific subset of the X-Y plane. Standard tests for independence are not suitable in such cases, and alternative tests that take the selection bias into account are required. Here, we generalize the notion of quasi-inde...
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作者：Dai, Ben; Shen, Xiaotong; Wong, Wing
作者单位：University of Minnesota System; University of Minnesota Twin Cities; Stanford University; Stanford University
摘要：Instance generation creates representative examples to interpret a learning model, as in regression and classification. For example, representative sentences of a topic of interest describe the topic specifically for sentence categorization. In such a situation, a large number of unlabeled observations may be available in addition to labeled data, for example, many unclassified text corpora (unlabeled instances) are available with only a few classified sentences (labeled instances). In this ar...
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作者：Fan, Jianqing; Fan, Yingying; Han, Xiao; Lv, Jinchi
作者单位：Princeton University; University of Southern California; Chinese Academy of Sciences; University of Science & Technology of China, CAS
摘要：Characterizing the asymptotic distributions of eigenvectors for large random matrices poses important challenges yet can provide useful insights into a range of statistical applications. To this end, in this article we introduce a general framework of asymptotic theory of eigenvectors for large spiked random matrices with diverging spikes and heterogeneous variances, and establish the asymptotic properties of the spiked eigenvectors and eigenvalues for the scenario of the generalized Wigner ma...
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作者：Fu, Luella; Gang, Bowen; James, Gareth M.; Sun, Wenguang
作者单位：California State University System; San Francisco State University; Fudan University; University of Southern California
摘要：Standardization has been a widely adopted practice in multiple testing, for it takes into account the variability in sampling and makes the test statistics comparable across different study units. However, despite conventional wisdom to the contrary, we show that there can be a significant loss in information from basing hypothesis tests on standardized statistics rather than the full data. We develop a new class of heteroscedasticity-adjusted ranking and thresholding (HART) rules that aim to ...
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作者：Xue, Fei; Tang, Xiwei; Kim, Grace; Koenen, Karestan C.; Martin, Chantel L.; Galea, Sandro; Wildman, Derek; Uddin, Monica; Qu, Annie
作者单位：Purdue University System; Purdue University; University of Virginia; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital; Harvard University; Harvard T.H. Chan School of Public Health; University of North Carolina; University of North Carolina Chapel Hill; Boston University; State University System of Florida; University of South Florida; University of California System; University of California Irvine
摘要：DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mechanism of PTSD for African Americans still remains unknown. To fill this gap, in this article, we investigate how DNAm mediates the effects of traumatic experiences on PTSD symptoms in the Detroit Neighborhood Health Study (DNHS) (2008-2013) which involves primarily African Americans adults. To achiev...
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作者：Liang, Tengyuan; Tran-Bach, Hai
作者单位：University of Chicago; University of Chicago
摘要：We use a connection between compositional kernels and branching processes via Mehler's formula to study deep neural networks. This new probabilistic insight provides us a novel perspective on the mathematical role of activation functions in compositional neural networks. We study the unscaled and rescaled limits of the compositional kernels and explore the different phases of the limiting behavior, as the compositional depth increases. We investigate the memorization capacity of the compositio...
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作者：Bu, Fan; Aiello, Allison E.; Xu, Jason; Volfovsky, Alexander
作者单位：Duke University; University of North Carolina; University of North Carolina Chapel Hill
摘要：We propose a generative model and an inference scheme for epidemic processes on dynamic, adaptive contact networks. Network evolution is formulated as a link-Markovian process, which is then coupled to an individual-level stochastic susceptible-infectious-recovered model, to describe the interplay between the dynamics of the disease spread and the contact network underlying the epidemic. A Markov chain Monte Carlo framework is developed for likelihood-based inference from partial epidemic obse...
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作者：Efron, Bradley
作者单位：Stanford University
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作者：Rosset, Saharon; Tibshirani, Ryan J.
作者单位：Tel Aviv University; Carnegie Mellon University
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作者：Dubey, Paromita; Muller, Hans-Georg
作者单位：Stanford University; University of California System; University of California Davis
摘要：Samples of dynamic or time-varying networks and other random object data such as time-varying probability distributions are increasingly encountered in modern data analysis. Common methods for time-varying data such as functional data analysis are infeasible when observations are time courses of networks or other complex non-Euclidean random objects that are elements of general metric spaces. In such spaces, only pairwise distances between the data objects are available and a strong limitation...
