515期

最新文章

• Analysis of Proportional Odds Models With Censoring and Errors-in-Covariates AI翻译
  作者：Sinha, Samiran; Ma, Yanyuan
  作者单位：Texas A&M University System; Texas A&M University College Station; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of South Carolina System; University of South Carolina Columbia
  摘要：We propose a consistent method for estimating both the finite- and infinite-dimensional parameters of the proportional odds model when a covariate is subject to measurement error and time-to-events are subject to right censoring. The proposed method does not rely on the distributional assumption of the true covariate, which is not observed in the data. In addition, the proposed estimator does not require the measurement error to be:normally distributed or to have any other specific distributio...
• Model-Based Geostatistics for Prevalence Mapping in Low-Resource Settings Comment AI翻译
  作者：Held, Leonhard; Muff, Stefanie
  作者单位：University of Zurich; Swiss School of Public Health (SSPH+)
• Graphical Procedures for Multiple Comparisons Under General Dependence AI翻译
  作者：Bennett, Christopher J.; Thompson, Brennan S.
  作者单位：Toronto Metropolitan University
  摘要：It has been more than half a century since Tukey first introduced graphical displays that relate nonoverlap of confidence intervals to statistically significant differences between parameter estimates. In this article, we show how Tukey's graphical overlap procedure can be modified to accommodate general forms of dependence within and across samples. We also develop a procedure that can be used to more effectively resolve rankings within the tails of the distributions of parameter values, ther...
• Conditional Sure Independence Screening AI翻译
  作者：Barut, Emre; Fan, Jianqing; Verhasselt, Anneleen
  作者单位：George Washington University; Princeton University; Fudan University; Hasselt University
  摘要：Independence screening is powerful for variable selection when the number of variables is massive. Commonly used independence screening methods are based on marginal correlations or its variants. When some prior knowledge on a certain important set of variables is available, a natural assessment on the relative importance of the other predictors is their conditional contributions to the response given the known set of variables. This results in conditional sure independence screening (CSIS). C...
• Fast Estimation of Regression Parameters in a Broken-Stick Model for Longitudinal Data AI翻译
  作者：Das, Ritabrata; Banerjee, Moulinath; Nan, Bin; Zheng, Huiyong
  作者单位：University of Michigan System; University of Michigan; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Estimation of change-point locations in the broken-stick model has significant applications in modeling important biological phenomena. In this article, we present a computationally economical likelihood-based approach for estimating change-point(s) efficiently in both cross-sectional and longitudinal settings. Our method, based on local smoothing in a shrinking neighborhood of each change-point, is shown via simulations to be computationally more viable than existing methods that rely on sear...
• Estimation of Directed Acyclic Graphs Through Two-Stage Adaptive Lasso for Gene Network Inference AI翻译
  作者：Han, Sung Won; Chen, Gong; Cheon, Myun-Seok; Zhong, Hua
  作者单位：Korea University; University System of Georgia; Georgia Institute of Technology; New York University
  摘要：Graphical models are a popular approach to find dependence and conditional independence relationships between gene expressions. Directed acyclic graphs (DAGs) are a special class of directed, graphical models, where all the edges are directed edges and contain. no directed cycles. The DAGs are well known models for discovering causal relationships between genes in gene regulatory networks. However, estimating DAGs without assuming known ordering is challenging due to high dimensionality, the a...
• Stabilized Nearest Neighbor Classifier and its Statistical Properties AI翻译
  作者：Sun, Will Wei; Qiao, Xingye; Cheng, Guang
  作者单位：Yahoo! Inc; University of Miami; State University of New York (SUNY) System; Binghamton University, SUNY; Purdue University System; Purdue University
  摘要：The stability of statistical analysis is an important indicator for reproducibility, which is one main principle of the scientific method. It entails that similar statistical conclusions can be reached based on independent samples from the same underlying population. In this article, we introduce a general measure of classification instability (CIS) to quantify the sampling variability of the prediction made by a classification method. Interestingly, the asymptotic CIS of any weighted nearest ...
• Bayesian Nonparametric Estimation for Dynamic Treatment Regimes With Sequential Transition Times Rejoinder AI翻译
  作者：Xu, Yanxun; Muller, Peter; Wahed, Abdus S.; Thall, Peter
  作者单位：University of Texas System; University of Texas Austin; University of Texas System; University of Texas Austin; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; University of Texas System; UTMD Anderson Cancer Center
• Bayesian Nonparametric Estimation for Dynamic Treatment Regimes With Sequential Transition Times Comment AI翻译
  作者：Trippa, Lorenzo; Parmigiani, Giovanni
  作者单位：Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Harvard University; Harvard T.H. Chan School of Public Health
• Model-Based Geostatistics for Prevalence Mapping in Low-Resource Settings Rejoinder AI翻译
  作者：Diggle, Peter J.; Giorgi, Emanuele
  作者单位：Lancaster University