2010

最新文章

• Second-Order Comparison of Gaussian Random Functions and the Geometry of DNA Minicircles AI翻译
  作者：Panaretos, Victor M.; Kraus, David; Maddocks, John H.
  作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
  摘要：Given two samples of continuous zero-mean iid Gaussian processes on [0, 1], we consider the problem of testing whether they share the same covariance structure. Our study is motivated by the problem of determining whether the mechanical properties of short strands of DNA are significantly affected by their base-pair sequence; though expected to be true, had so far not been observed in three-dimensional electron microscopy data, The testing problem is seen to involve aspects of ill-posed invers...
• Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data AI翻译
  作者：Baladandayuthapani, Veerabhadran; Ji, Yuan; Talluri, Rajesh; Nieto-Barajas, Luis E.; Morris, Jeffrey S.
  作者单位：University of Texas System; UTMD Anderson Cancer Center; University of Texas System; UTMD Anderson Cancer Center; Texas A&M University System; Texas A&M University College Station; Instituto Tecnologico Autonomo de Mexico
  摘要：Array-based comparative genomic hybridization (aCGH) is a high-resolution, high-throughput technique for studying the genetic basis of cancer. The resulting data consist of log fluorescence ratios as a function of the genomic DNA location and provide a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimating the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most curre...
• Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection AI翻译
  作者：Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry
  作者单位：Texas A&M University System; Texas A&M University College Station; Fred Hutchinson Cancer Center; Texas A&M University System; Texas A&M University College Station
  摘要：Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model...
• Using Calibration Weighting to Adjust for Nonignorable Unit Nonresponse AI翻译
  作者：Kott, Phillip S.; Chang, Ted
  作者单位：Research Triangle Institute; University of Virginia
  摘要：When calibration weighting is be used to adjust for unit nonresponse in a sample survey, the response/nonresponse mechanism is often assumed to be a function of a set of covariates, which we call model variables. These model variables usually also serve as the benchmark variables in the calibration equation. In principle, however, the model variables do not have to coincide with the benchmark variables. Since the model-variable values need only be known for the respondents, this allows the tre...
• Using a Short Screening Scale for Small-Area Estimation of Mental Illness Prevalence for Schools AI翻译
  作者：Li, Fan; Zaslavsky, Alan M.
  作者单位：Duke University; Harvard University; Harvard Medical School
  摘要：We use data collected in the National Comorbidity Survey-Adolescent (NCS-A) to develop a methodology to estimate the small-area prevalence of serious emotional distress (SED) in schools in the United States, exploiting the clustering of the main NCS-A sample by school. The NCS-A instrument includes both a short screening scale, the K6, and extensive diagnostic assessments of the individual disorders and associated impairment that determine the diagnosis of SED. We fitted a Bayesian bivariate m...
• Nonparametric Regression With Missing Outcomes Using Weighted Kernel Estimating Equations AI翻译
  作者：Wang, Lu; Rotnitzky, Andrea; Lin, Xihong
  作者单位：University of Michigan System; University of Michigan; Harvard University; Harvard T.H. Chan School of Public Health; Universidad Torcuato Di Tella
  摘要：We consider nonparametric regression of a scalar outcome on a covariate when the outcome is missing at random (MAR) given the covariate and other observed auxiliary variables. We propose a class of augmented inverse probability weighted (AIPW) kernel estimating equations for nonparametric regression under MAR. We show that AIPW kernel estimators are consistent when the probability that the outcome is observed, that is, the selection probability, is either known by design or estimated under a c...
• Bayesian Multiscale Multiple Imputation With Implications for Data Confidentiality AI翻译
  作者：Holan, Scott H.; Toth, Daniell; Ferreira, Marco A. R.; Karr, Alan F.
  作者单位：University of Missouri System; University of Missouri Columbia; United States Department of Labor
  摘要：Many scientific, sociological, and economic applications present data that are collected on multiple scales of resolution. One particular form of multiscale data arises when data are aggregated across different scales both longitudinally and by economic sector. Frequently, such datasets experience missing observations in a manner that they can be accurately imputed, while respecting the constraints imposed by the multiscale nature of the data, using the method we propose known as Bayesian mult...
• Multivariate Outlier Detection With High-Breakdown Estimators AI翻译
  作者：Cerioli, Andrea
  作者单位：University of Parma
  摘要：In this paper we develop multivariate outlier tests based on the high-breakdown Minimum Covariance Determinant estimator The rules that we propose have good performance under the null hypothesis of no outliers in the data and also appreciable power properties for the purpose of individual outlier detection This achievement is made possible by two orders of improvement over the currently available methodology First we suggest an approximation to the exact distribution of robust distances flour ...
• Inference in Semiparametric Regression Models Under Partial Questionnaire Design and Nonmonotone Missing Data AI翻译
  作者：Chatterjee, Nilanjan; Li, Yan
  作者单位：National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI); NIH National Cancer Institute- Division of Cancer Epidemiology & Genetics; University of Texas System; University of Texas Arlington
  摘要：In epidemiologic studies, partial questionnaire design (PQD) can reduce cost, time, and other practical burdens associated with lengthy questionnaires by assigning different subsets of the questionnaire to different, but overlapping, subsets of the study participants. In this article, we describe methods for semiparametric inference for regression model under PQD and other study settings that can generate nonmonotone missing data in covariates. In particular, motivated from methods for multiph...
• Grouping Pursuit Through a Regularization Solution Surface AI翻译
  作者：Shen, Xiaotong; Huang, Hsin-Cheng
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; Academia Sinica - Taiwan
  摘要：Extracting grouping structure or identifying homogenous subgroups of predictors in regression is crucial for high-dimensional data analysis. A low-dimensional structure in particular-grouping, when captured in a regression model-enables to enhance predictive performance and to facilitate a model's interpretability. Grouping pursuit extracts homogenous subgroups of predictors most responsible for outcomes of a response. This is the case in gene network analysis, where grouping reveals gene func...