2011

最新文章

• Inference for Quantitation Parameters in Polymerase Chain Reactions via Branching Processes With Random Effects AI翻译
  作者：Hanlon, Bret; Vidyashankar, Anand N.
  作者单位：University of Wisconsin System; University of Wisconsin Madison
  摘要：The quantitative polymerase chain reaction (qPCR) is a widely used tool for gene quantitation and has been applied extensively in several scientific areas. The current methods used for analyzing qPCR data fail to account for multiple sources of variability present in the PCR dynamics, leading to biased estimates and incorrect inference. In this article, we introduce a branching process model with random effects to account for within-reaction and between-reaction variability in PCR experiments....
• Predictive Inference for Integrated Volatility AI翻译
  作者：Corradi, Valentina; Distaso, Walter; Swanson, Norman R.
  作者单位：University of Warwick; Imperial College London; Rutgers University System; Rutgers University New Brunswick
  摘要：Numerous volatility-based derivative products have been engineered in recent years. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this article we propose nonparametric estimators of the aforementioned quantities, based on model-free volatility estimators. We establish consistency and asymptotic normality for the feasible estimators and study their finite-sample properties through a Monte Carlo experiment. Finall...
• Large-Scale Correlation Screening AI翻译
  作者：Hero, Alfred; Rajaratnam, Bala
  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; Stanford University
  摘要：This article addresses the problem of screening for variables with high correlations in high-dimensional data in which there can be many fewer samples than variables. We focus on threshold-based correlation screening methods for three related applications: screening for variables with large correlations within a single treatment (autocorrelation screening), screening for variables with large cross-correlations over two treatments (cross-correlation screening), and screening for variables that ...
• A Statistical Framework for the Analysis of ChIP-Seq Data AI翻译
  作者：Kuan, Pei Fen; Chung, Dongjun; Pan, Guangjin; Thomson, James A.; Stewart, Ron; Keles, Suenduez
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; Chinese Academy of Sciences; Guangzhou Institute of Biomedicine & Health, CAS; Chinese Academy of Sciences; University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison; The Morgridge Institute for Research, Inc.
  摘要：Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins, histone modifications, and nucleosome occupancy. As the cost of sequencing is decreasing, many researchers are switching from microarray-based technologies (ChIP-chip) to ChIP-Seq for genome-wide study of transcriptional regulation. Despite its increasing and well-deserved popularity, there is little work that investigates and accounts for sources ...
• Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging AI翻译
  作者：Lee, Seonjoo; Shen, Haipeng; Truong, Young; Lewis, Mechelle; Huang, Xuemei
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Penn State Health
  摘要：Independent component analysis (ICA) is an effective data-driven method for blind source separation. It has been successfully applied to separate source signals of interest from their mixtures. Most existing ICA procedures are carried out by relying solely on the estimation of the marginal density functions, either parametrically or nonparametrically. In many applications, correlation structures within each source also play an important role besides the marginal distributions. One important ex...
• Saddlepoint Test in Measurement Error Models AI翻译
  作者：Ma, Yanyuan; Ronchetti, Elvezio
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Geneva; University of Geneva
  摘要：We develop second-order hypothesis testing procedures in functional measurement error models for small or moderate sample sizes, where the classical first-order asymptotic analysis often fails to provide accurate results. In functional models no distributional assumptions are made on the unobservable covariates and this leads to semiparametric models. Our testing procedure is derived using saddlepoint techniques and is based on an empirical distribution estimation subject to the null hypothesi...
• A Direct Estimation Approach to Sparse Linear Discriminant Analysis AI翻译
  作者：Cai, Tony; Liu, Weidong
  作者单位：University of Pennsylvania; Shanghai Jiao Tong University; Shanghai Jiao Tong University
  摘要：This article considers sparse linear discriminant analysis of high-dimensional data. In contrast to the existing methods which are based on separate estimation of the precision matrix Omega and the difference delta of the mean vectors, we introduce a simple and effective classifier by estimating the product Omega delta directly through constrained l(1) minimization. The estimator can be implemented efficiently using linear programming and the resulting classifier is called the linear programmi...
• Summarizing Insurance Scores Using a Gini Index AI翻译
  作者：Frees, Edward W.; Meyers, Glenn; Cummings, A. David
  作者单位：University of Wisconsin System; University of Wisconsin Madison
  摘要：Individuals, corporations and government entities regularly exchange financial risks y at prices Pi. Comparing distributions of risks and prices can be difficult, particularly when the financial risk distribution is complex. For example, with insurance, it is not uncommon for a risk distribution to be a mixture of 0's (corresponding to no claims) and a right-skewed distribution with thick tails (the claims distribution). However, analysts do not work in a vacuum, and in the case of insurance t...
• An Outlier-Robust Fit for Generalized Additive Models With Applications to Disease Outbreak Detection AI翻译
  作者：Alimadad, Azadeh; Salibian-Barrera, Matias
  作者单位：Simon Fraser University; Simon Fraser University; University of British Columbia
  摘要：We are interested in a class of unsupervised methods to detect possible disease outbreaks, that is, rapid increases in the number of cases of a particular disease that deviate from the pattern observed in the past. The motivating application for this article deals with detecting outbreaks using generalized additive models (GAMs) to model weekly counts of certain infectious diseases. We can use the distance between the predicted and observed counts for a specific week to determine whether an im...
• Projection Estimators for Generalized Linear Models AI翻译
  作者：Bergesio, Andrea; Yohai, Victor J.
  作者单位：Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); National University of the Littoral; University of Buenos Aires
  摘要：We introduce a new class of robust estimators for generalized linear models which is an extension of the class of projection estimators for linear regression. These projection estimators are defined using an initial robust estimator for a generalized linear model with only one unknown parameter. We found a bound for the maximum asymptotic bias of the projection estimator caused by a fraction epsilon of outlier contamination. For small epsilon, this bias is approximately twice the maximum bias ...