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作者：Zhang, Xuefei; Xu, Gongjun; Zhu, Ji
作者单位：University of Michigan System; University of Michigan
摘要：Network latent space models assume that each node is associated with an unobserved latent position in a Euclidean space, and such latent variables determine the probability of two nodes connecting with each other. In many applications, nodes in the network are often observed along with high-dimensional node variables, and these node variables provide important information for understanding the network structure. However, classical network latent space models have several limitations in incorpo...
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作者：Wang, Jianqiao; Li, Hongzhe
作者单位：University of Pennsylvania
摘要：Genome-wide association studies have identified thousands of genetic variants that are associated with complex traits. Many complex traits are shown to share genetic etiology. Although various genetic correlation measures and their estimators have been developed, rigorous statistical analysis of their properties, including their robustness to model assumptions, is still lacking. We develop a method of moments estimator of genetic correlation between two traits in the framework of high-dimensio...
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作者：Vats, D.; Goncalves, F. B.; Latuszynski, K.; Roberts, G. O.
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Kanpur; Universidade Federal de Minas Gerais; University of Warwick
摘要：Accept-reject-based Markov chain Monte Carlo algorithms have traditionally utilized acceptance probabilities that can be explicitly written as a function of the ratio of the target density at the two contested points. This feature is rendered almost useless in Bayesian posteriors with unknown functional forms. We introduce a new family of Markov chain Monte Carlo acceptance probabilities that has the distinguishing feature of not being a function of the ratio of the target density at the two p...
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作者：Chang, Jinyuan; Cheng, Guanghui; Yao, Qiwei
作者单位：Southwestern University of Finance & Economics - China; Guangzhou University; University of London; London School Economics & Political Science
摘要：We propose a new unit-root test for a stationary null hypothesis H-0 against a unit-root alternative H-1. Our approach is nonparametric as H-0 assumes only that the process concerned is I(0), without specifying any parametric forms. The new test is based on the fact that the sample autocovariance function converges to the finite population autocovariance function for an I(0) process, but diverges to infinity for a process with unit roots. Therefore, the new test rejects H-0 for large values of...
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作者：Tan, Falong; Zhu, Lixing
作者单位：Hunan University; Beijing Normal University; Beijing Normal University Zhuhai
摘要：The classical integrated conditional moment test is a promising method for model checking and its basic idea has been applied to develop several variants. However, in diverging-dimension scenarios, the integrated conditional moment test may break down and has completely different limiting properties from the fixed-dimension case. Furthermore, the related wild bootstrap approximation can also be invalid. To extend this classical test to diverging dimension settings, we propose a projected adapt...
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作者：Zhao, Anqi; Ding, Peng
作者单位：National University of Singapore; University of California System; University of California Berkeley
摘要：Factorial designs are widely used because of their ability to accommodate multiple factors simultaneously. Factor-based regression with main effects and some interactions is the dominant strategy for downstream analysis, delivering point estimators and standard errors simultaneously via one least-squares fit. Justification of these convenient estimators from the design-based perspective requires quantifying their sampling properties under the assignment mechanism while conditioning on the pote...
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作者：Sarkar, Sanat K.; Tang, Cheng Yong
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
摘要：We consider the knockoff-based multiple testing set-up of Barber & Candes (2015). for variable selection in multiple regression. The method of Benjamini & Hochberg (1995) and an adaptive version of it are adjusted to this set-up, transforming them to valid p-value-based, false discovery rate-controlling methods that do not rely on specifying the correlation structure of the explanatory variables. Simulations and real data applications show that the proposed methods are powerful competitors of ...
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作者：Vats, D.; Flegal, J. M.
作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Kanpur; University of California System; University of California Riverside
摘要：Lag windows are commonly used in time series analysis, econometrics, steady-state simulation and Markov chain Monte Carlo to estimate time-average covariance matrices. In the presence of positive correlation in the underlying process, estimators of this matrix almost always exhibit significant negative bias, leading to undesirable finite-sample properties. We propose a new family of lag windows specifically designed to improve finite-sample performance by offsetting this negative bias. Any exi...
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作者：Zhang, Yuqian; Bradic, Jelena
作者单位：Renmin University of China; University of California System; University of California San Diego
摘要：Afundamental challenge in semi-supervised learning lies in the observed data's disproportional size when compared with the size of the data collected with missing outcomes. An implicit understanding is that the dataset with missing outcomes, being significantly larger, ought to improve estimation and inference. However, it is unclear to what extent this is correct. We illustrate one clear benefit: root-n inference of the outcome's mean is possible while only requiring a consistent estimation o...
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作者：Guinness, Joseph
作者单位：Cornell University
摘要：We conduct a study of the aliased spectral densities of Matern covariance functions on a regular grid of points, elucidating the properties of a popular approximation based on stochastic partial differential equations. While other researchers have shown that this approximation can work well for the covariance function, we find that it assigns too much power at high frequencies and does not provide increasingly accurate approximations to the inverse as the grid spacing goes to zero, except in t...
