510期

最新文章

• Testing Hypotheses of Covariate-Adaptive Randomized Clinical Trials AI翻译
  作者：Ma, We; Hu, Feifang; Zhang, Lixin
  作者单位：University of Virginia; George Washington University; Zhejiang University
  摘要：Covariate-adaptive designs are often implemented to balance important covariates in clinical trials. However, the theoretical properties of conventional testing hypotheses are usually unknown under covariate-adaptive randomized clinical trials. In the literature, most studies are based on simulations. In this article, we provide theoretical foundation of hypothesis testing under covariate-adaptive designs based on linear models. We derive the asymptotic distributions of the test statistics of ...
• Nonpararnetric K-Sample Tests via Dynamic Slicing AI翻译
  作者：Jiang, Bo; Ye, Chao; Liu, Jun S.
  作者单位：Harvard University; Tsinghua University; Tsinghua University; Tsinghua University; Harvard University
  摘要：K-sample testing problems arise in many scientific applications and have attracted statisticians' attention for many years. We propose an omnibus nonparametric method based on an optimal discretization (aka slicing) of continuous random variables in the test. The novelty of our approach lies in the inclusion of a term penalizing the number of slices (i.e., the resolution of the discretization) so as to regularize the corresponding likelihood-ratio test statistic. An efficient dynamic programmi...
• Scalable Bayesian Model Averaging Through Local Information Propagation AI翻译
  作者：Ma, Li
  作者单位：Duke University
  摘要：This article shows that a probabilistic version of the classical forward-stepwise variable inclusion procedure can serve as a general data-augmentation scheme for model space distributions in (generalized) linear models. This latent variable representation takes the form of a Markov process, thereby allowing information propagation algorithms to be applied for sampling from model space posteriors. In particular, We propose a sequential Monte Carlo method for achieving effective unbiased Bayesi...
• Functional and Structural Methods With Mixed Measurement Error and Misclassification in Covariates AI翻译
  作者：Yi, Grace Y.; Ma, Yanyuan; Spiegelman, Donna; Carroll, Raymond J.
  作者单位：University of Waterloo; Texas A&M University System; Texas A&M University College Station; Harvard University; Harvard T.H. Chan School of Public Health; Texas A&M University System; Texas A&M University College Station; University of Technology Sydney
  摘要：Covariate measurement imprecision or errors arise frequently in many areas. It is well known that ignoring such errors can substantially degrade the quality of inference or even yield erroneous results. Although in practice both covariates subject to measurement error and covariates subject to misclassification can occur, research attention in the literature has mainly focused on addressing either one of these problems separately. To fill this gap, we develop estimation and inference methods t...
• Clustering From Categorical Data Sequences AI翻译
  作者：Crane, Harry
  作者单位：Rutgers University System; Rutgers University New Brunswick
  摘要：The three-parameter cluster model is a combinatorial stochastic process that generates categorical response sequences by randomly perturbing a fixed clustering parameter. This clear relationship between the observed data and the underlying clustering is particularly attractive in cluster analysis, in which supervised learning is a common goal and missing data is a familiar issue. The model is well equipped for this task, as it can handle missing data, perform out-of-sample inference, and accom...
• A Two-Sample Test for Equality of Means in High Dimension AI翻译
  作者：Gregory, Karl Bruce; Carroll, Raymond J.; Baladandayuthapani, Veerabhadran; Lahiri, Soumendra N.
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Texas System; UTMD Anderson Cancer Center; North Carolina State University
  摘要：We develop a test statistic for testing the equality of two population mean vectors in the large-p-small-n setting. Such a test must surmount the rank-deficiency of the sample covariance matrix, which breaks down the classic Hotel ling T-2 test. The proposed procedure, called the generalized component test, avoids full estimation of the covariance matrix by assuming that the p components admit a logical ordering such that the dependence between components is related to their displacement. The ...
• Survival Analysis of Lob lolly Pine Trees With Spatially Correlated Random Effects AI翻译
  作者：Li, Jie; Hong, Yili; Thapa, Ram; Burkhart, Harold E.
  作者单位：Virginia Polytechnic Institute & State University; Virginia Polytechnic Institute & State University
  摘要：Loblolly pine, a native pine species of the southeastern United States, is the most-planted species for commercial timber. Predicting survival of loblolly pine following planting is of great interest to researchers in forestry science as it is closely related to the yield of timber. Data were collected from a region-wide thinning study, where permanent plots, located at 182 sites ranging from central Texas east to Florida and north to Delaware, were established in 1980-1981. One of the main ob...
• Efficient Quantile Regression Analysis With Missing Observations AI翻译
  作者：Chen, Xuerong; Wan, Alan T. K.; Zhou, Yong
  作者单位：Georgetown University; City University of Hong Kong; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Shanghai University of Finance & Economics
  摘要：This article examines the problem of estimation in a quantile regression model when observations are missing at random under independent and nonidentically distributed errors. We consider three approaches of handling this problem based on nonparametric inverse probability weighting, estimating equations projection, and a combination of both. An important distinguishing feature of our methods is their ability to handle missing response and/or partially missing covariates, whereas existing techn...
• Likelihood Ratio Test for Multi-Sample Mixture Model and Its Application to Genetic Imprinting AI翻译
  作者：Li, Shaoting; Chen, Jiahua; Guo, Jianhua; Jing, Bing-Yi; Tsang, Shui-Ying; Xue, Hong
  作者单位：Northeast Normal University - China; Northeast Normal University - China; University of British Columbia; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology; Hong Kong University of Science & Technology
  摘要：Genomic imprinting is a known aspect of the etiology of many diseases. The imprinting phenomenon depicts differential expression levels of the allele depending on its parental origin. When the parental origin is unknown, the expression level has a finite normal mixture distribution. In such applications, a random sample of expression levels consists of three subsamples according to the number of minor alleles an individual possesses, of which one is the mixture and the other two are homogeneou...
• Matching a Distribution by Matching Quantiles Estimation AI翻译
  作者：Sgouropoulos, Nikolaos; Yao, Qiwei; Yastremiz, Claudia
  作者单位：University of London; London School Economics & Political Science; Peking University; Bank of England
  摘要：Motivated by the problem of selecting representative portfolios for backtesting counterparty credit risks, we propose a matching quantiles estimation (MQE) method for matching a target distribution by that of a linear combination of a set of random variables. An iterative procedure based on the ordinary least-squares estimation (OLS) is proposed to compute MQE. MQE can be easily modified by adding a LASSO penalty term if a sparse representation is desired, or by restricting the matching within...