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作者：Chen, Jie; Stein, Michael L.
作者单位：International Business Machines (IBM); IBM USA; Rutgers University System; Rutgers University New Brunswick
摘要：Gaussian random fields (GRF) are a fundamental stochastic model for spatiotemporal data analysis. An essential ingredient of GRF is the covariance function that characterizes the joint Gaussian distribution of the field. Commonly used covariance functions give rise to fully dense and unstructured covariance matrices, for which required calculations are notoriously expensive to carry out for large data. In this work, we propose a construction of covariance functions that result in matrices with...
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作者：Giordano, Sabrina
作者单位：University of Calabria
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作者：Saha, Arkajyoti; Basu, Sumanta; Datta, Abhirup
作者单位：Johns Hopkins University; Cornell University
摘要：Spatial linear mixed-models, consisting of a linear covariate effect and a Gaussian process (GP) distributed spatial random effect, are widely used for analyses of geospatial data. We consider the setting where the covariate effect is nonlinear. Random forests (RF) are popular for estimating nonlinear functions but applications of RF for spatial data have often ignored the spatial correlation. We show that this impacts the performance of RF adversely. We propose RF-GLS, a novel and well-princi...
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作者：Xie, Fangzheng; Xu, Yanxun
作者单位：Indiana University System; Indiana University Bloomington; Johns Hopkins University
摘要：We propose a one-step procedure to estimate the latent positions in random dot product graphs efficiently. Unlike the classical spectral-based methods, the proposed one-step procedure takes advantage of both the low-rank structure of the expected adjacency matrix and the Bernoulli likelihood information of the sampling model simultaneously. We show that for each vertex, the corresponding row of the one-step estimator (OSE) converges to a multivariate normal distribution after proper scaling an...
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作者：Sun, Cheng-Yu; Tang, Boxin
作者单位：Simon Fraser University
摘要：We explore the connections between uniform projection designs and strong orthogonal arrays of strength 2+ in this article. Both of these classes of designs are suitable designs for computer experiments and space-filling in two-dimensional margins, but they are motivated by different considerations. Uniform projection designs are introduced by Sun, Wang, and Xu to capture two-dimensional uniformity using the centered L-2-discrepancy whereas strong orthogonal arrays of strength 2+ are brought fo...
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作者：Song, Xiaoyu; Ji, Jiayi; Wang, Pei
作者单位：Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai; Icahn School of Medicine at Mount Sinai
摘要：Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over six million deaths in the ongoing COVID-19 pandemic. SARS-CoV-2 uses ACE2 protein to enter human cells, raising a pressing need to characterize proteins/pathways interacted with ACE2. Large-scale proteomic profiling technology is not mature at single-cell resolution to examine the protein activities in disease-relevant cell types. We propose iProMix, a novel statistical framework to identify epithelial-cell specific a...
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作者：Deng, Yujia; Tang, Xiwei; Qu, Annie
作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Virginia; University of California System; University of California Irvine
摘要：Multi-dimensional tensor data have gained increasing attention in the recent years, especially in biomedical imaging analyses. However, the most existing tensor models are only based on the mean information of imaging pixels. Motivated by multimodal optical imaging data in a breast cancer study, we develop a new tensor learning approach to use pixel-wise correlation information, which is represented through the higher order correlation tensor. We proposed a novel semi-symmetric correlation ten...
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作者：Henzi, Alexander; Kleger, Gian-Reto; Ziegel, Johanna F.
作者单位：University of Bern; Kantonsspital St. Gallen
摘要：A Distributional (Single) Index Model (DIM) is a semiparametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method is a combination of classical single-index models for the estimation of the conditional mean of a response given covariates, and isotonic distributional regression. The model for the index is parametric, whereas the conditional distributions are estimated nonparametrically under a stochastic ordering constraint. We sh...
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作者：Zhu, Wanchuang; Jiang, Yingkai; Liu, Jun S.; Deng, Ke
作者单位：Tsinghua University; Tsinghua University; Tsinghua University; Tsinghua University; Harvard University
摘要：Learning how to aggregate ranking lists has been an active research area for many years and its advances have played a vital role in many applications ranging from bioinformatics to internet commerce. The problem of discerning reliability of rankers based only on the rank data is of great interest to many practitioners, but has received less attention from researchers. By dividing the ranked entities into two disjoint groups, that is, relevant and irrelevant/background ones, and incorporating ...
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作者：Simpson, Matthew; Holan, Scott H.; Wikle, Christopher K.; Bradley, Jonathan R.
作者单位：SAS Institute Inc; University of Missouri System; University of Missouri Columbia; State University System of Florida; Florida State University
摘要：The presence of income inequality is an important problem to demographers, policy makers, economists, and social scientists. A causal link has been hypothesized between income inequality and income segregation, which measures how much households with similar incomes cluster. The information theory index is used to measure income segregation, however, critics have suggested the divergence index instead. Motivated by this, we construct both indices using American Community Survey (ACS) estimates...
