534期

最新文章

• The Effects of Stringent and Mild Interventions for Coronavirus Pandemic AI翻译
  作者：Tian, Ting; Tan, Jianbin; Luo, Wenxiang; Jiang, Yukang; Chen, Minqiong; Yang, Songpan; Wen, Canhong; Pan, Wenliang; Wang, Xueqin
  作者单位：Sun Yat Sen University; Chinese Academy of Sciences; University of Science & Technology of China, CAS
  摘要：The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and social importance to evaluate the effects of interventions in the pandemic of COVID-19. With the help of a synthetic control method, the regression discontinuity, and a state-space compartmental model, we evaluated the treatment and stagewise effects of the intervention policies. We found statistically significant treatme...
• More Efficient Policy Learning via Optimal Retargeting AI翻译
  作者：Kallus, Nathan
  作者单位：Cornell University; Cornell University
  摘要：Policy learning can be used to extract individualized treatment regimes from observational data in healthcare, civics, e-commerce, and beyond. One big hurdle to policy learning is a commonplace lack of overlap in the data for different actions, which can lead to unwieldy policy evaluation and poorly performing learned policies. We study a solution to this problem based on retargeting, that is, changing the population on which policies are optimized. We first argue that at the population level,...
• Global and Simultaneous Hypothesis Testing for High-Dimensional Logistic Regression Models AI翻译
  作者：Ma, Rong; Cai, T. Tony; Li, Hongzhe
  作者单位：University of Pennsylvania; University of Pennsylvania
  摘要：High-dimensional logistic regression is widely used in analyzing data with binary outcomes. In this article, global testing and large-scale multiple testing for the regression coefficients are considered in both single- and two-regression settings. A test statistic for testing the global null hypothesis is constructed using a generalized low-dimensional projection for bias correction and its asymptotic null distribution is derived. A lower bound for the global testing is established, which sho...
• Intrinsic Wavelet Regression for Curves of Hermitian Positive Definite Matrices AI翻译
  作者：Chau, Joris; von Sachs, Rainer
  作者单位：Universite Catholique Louvain
  摘要：Intrinsic wavelet transforms and wavelet estimation methods are introduced for curves in the non-Euclidean space of Hermitian positive definite matrices, with in mind the application to Fourier spectral estimation of multivariate stationary time series. The main focus is on intrinsic average-interpolation wavelet transforms in the space of positive definite matrices equipped with an affine-invariant Riemannian metric, and convergence rates of linear wavelet thresholding are derived for intrins...
• Exponential-Family Embedding With Application to Cell Developmental Trajectories for Single-Cell RNA-Seq Data AI翻译
  作者：Lin, Kevin Z.; Lei, Jing; Roeder, Kathryn
  作者单位：University of Pennsylvania; Carnegie Mellon University
  摘要：Scientists often embed cells into a lower-dimensional space when studying single-cell RNA-seq data for improved downstream analyses such as developmental trajectory analyses, but the statistical properties of such nonlinear embedding methods are often not well understood. In this article, we develop the exponential-family SVD (eSVD), a nonlinear embedding method for both cells and genes jointly with respect to a random dot product model using exponential-family distributions. Our estimator use...
• Graphical Models for Processing Missing Data AI翻译
  作者：Mohan, Karthika; Pearl, Judea
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Los Angeles
  摘要：This article reviews recent advances in missing data research using graphical models to represent multivariate dependencies. We first examine the limitations of traditional frameworks from three different perspectives: transparency, estimability, and testability. We then show how procedures based on graphical models can overcome these limitations and provide meaningful performance guarantees even when data are missing not at random (MNAR). In particular, we identify conditions that guarantee c...
• Bias and High-Dimensional Adjustment in Observational Studies of Peer Effects AI翻译
  作者：Eckles, Dean; Bakshy, Eytan
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Facebook Inc
  摘要：Peer effects, in which an individual's behavior is affected by peers' behavior, are posited by multiple theories in the social sciences. Randomized field experiments that identify peer effects, however, are often expensive or infeasible, so many studies of peer effects use observational data, which is expected to suffer from confounding. Here we show, in the context of information and media diffusion, that high-dimensional adjustment of a nonexperimental control group (660 million observations...
• Privacy-Preserving Parametric Inference: A Case for Robust Statistics AI翻译
  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...
• Parametric Modeling of Quantile Regression Coefficient Functions With Longitudinal Data AI翻译
  作者：Frumento, Paolo; Bottai, Matteo; Fernandez-Val, Ivan
  作者单位：University of Pisa; Karolinska Institutet; Boston University
  摘要：In ordinary quantile regression, quantiles of different order are estimated one at a time. An alternative approach, which is referred to as quantile regression coefficients modeling (qrcm), is to model quantile regression coefficients as parametric functions of the order of the quantile. In this article, we describe how the qrcm paradigm can be applied to longitudinal data. We introduce a two-level quantile function, in which two different quantile regression models are used to describe the (c...
• Nonbifurcating Phylogenetic Tree Inference via the Adaptive LASSO AI翻译
  作者：Zhang, Cheng; Dinh, Vu; Matsen, Frederick A.
  作者单位：Peking University; Peking University; University of Delaware; Fred Hutchinson Cancer Center
  摘要：Phylogenetic tree inference using deep DNA sequencing is reshaping our understanding of rapidly evolving systems, such as the within-host battle between viruses and the immune system. Densely sampled phylogenetic trees can contain special features, including sampled ancestors in which we sequence a genotype along with its direct descendants, and polytomies in which multiple descendants arise simultaneously. These features are apparent after identifying zero-length branches in the tree. However...