2011

最新文章

• Nonparametric Regression With Predictors Missing at Random AI翻译
  作者：Efromovich, Sam
  摘要：Nonparametric regression with predictors missing at random (MAR), where the probability of missing depends only on observed variables, is considered. Univariate predictor is the primary case of interest. A new adaptive orthogonal series estimator is developed. Large sample theory shows that the estimator is rate-minimax and it is also sharp-minimax whenever predictors are missing completely at random (MCAR). Furthermore, confidence bands, estimation of nuisance functions, including conditional...
• Predicting False Discovery Proportion Under Dependence AI翻译
  作者：Ghosal, Subhashis; Roy, Anindya
  作者单位：North Carolina State University; University System of Maryland; University of Maryland Baltimore County
  摘要：We present a flexible framework for predicting error measures in multiple testing situations under dependence. Our approach is based on modeling the distribution of the probit transform of the p-values by mixtures of multivariate skew-normal distributions. The model can incorporate dependence among p-values and it allows for shape restrictions on the p-value density. A nonparametric Bayesian scheme for estimating the components of the mixture model is outlined and Markov chain Monte Carlo algo...
• Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models AI翻译
  作者：Fan, Jianqing; Feng, Yang; Song, Rui
  作者单位：Princeton University; Columbia University; Colorado State University System; Colorado State University Fort Collins
  摘要：A variable screening procedure via correlation learning was proposed by Fan and Lv (2008) to reduce dimensionality in sparse ultra-high-dimensional models. Even when the true model is linear, the marginal regression can be highly nonlinear. To address this issue, we further extend the correlation learning to marginal nonparametric learning. Our nonparametric independence screening (NIS) is a specific type of sure independence screening. We propose several closely related variable screening pro...
• Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation AI翻译
  作者：Gile, Krista J.
  作者单位：University of Massachusetts System; University of Massachusetts Amherst
  摘要：Respondent-driven sampling is a form of link-tracing network sampling, which is widely used to study hard-to-reach populations, often to estimate population proportions. Previous treatments of this process have used a with-replacement approximation, which we show induces bias in estimates for large sample fractions and differential network connectedness by characteristic of interest. We present a treatment of respondent-driven sampling as a successive sampling process. Unlike existing represen...
• Changepoints in the North Atlantic Tropical Cyclone Record AI翻译
  作者：Robbins, Michael W.; Lund, Robert B.; Gallagher, Colin M.; Lu, Qiqi
  作者单位：Clemson University; Mississippi State University
  摘要：This article examines the North Atlantic tropical cyclone record for statistical discontinuities (changepoints). This is a controversial area and indeed, our end conclusions are opposite of those made in Dr. Kelvin Droegemeier's July 28, 2009 Senate testimonial. The methods developed here should help rigorize the debate. Elaborating, we develop a level-alpha test for a changepoint in a categorical data sequence sampled from a multinomial distribution. The proposed test statistic is the maximum...
• Predicting Viral Infection From High-Dimensional Biomarker Trajectories AI翻译
  作者：Chen, Minhua; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S.; Lucas, Joseph; Dunson, David; Carin, Lawrence
  作者单位：Duke University; Duke University; Duke University; Duke University
  摘要：There is often interest in predicting an individual's latent health status based on high-dimensional biomarkers that vary over time. Motivated by time-course gene expression array data that we have collected in two influenza challenge studies performed with healthy human volunteers, we develop a novel time-aligned Bayesian dynamic factor analysis methodology. The time course trajectories in the gene expressions are related to a relatively low-dimensional vector of latent factors, which vary dy...
• Semiparametric Bayesian Modeling of Income Volatility Heterogeneity AI翻译
  作者：Jensen, Shane T.; Shore, Stephen H.
  作者单位：University of Pennsylvania; University System of Georgia; Georgia State University
  摘要：Research on income risk typically treats its proxy-income volatility, the expected magnitude of income changes-as if it were unchanged for an individual over time, the same for everyone at a point in time, or both. In reality, income risk evolves over time, and some people face more of it than others. To model heterogeneity and dynamics in (unobserved) income volatility, we develop a novel semiparametric Bayesian stochastic volatility model. Our Markovian hierarchical Dirichlet process (MHDP) ...
• Geostatistical Model Averaging for Locally Calibrated Probabilistic Quantitative Precipitation Forecasting AI翻译
  作者：Kleiber, William; Raftery, Adrian E.; Gneiting, Tilmann
  作者单位：National Center Atmospheric Research (NCAR) - USA; University of Washington; University of Washington Seattle; Ruprecht Karls University Heidelberg
  摘要：Accurate weather benefit many key societal functions and activities, including agriculture, transportation, recreation, and basic human and infrastructural safety. Over the past two decades, ensembles of numerical weather prediction models have been developed, in which multiple estimates of the current state of the atmosphere are used to generate probabilistic forecasts for future weather events. However, ensemble systems are uncalibrated and biased, and thus need to be statistically postproce...
• Fast and Accurate Approximation to Significance Tests in Genome-Wide Association Studies AI翻译
  作者：Zhang, Yu; Liu, Jun S.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; Harvard University
  摘要：Genome-wide association studies commonly involve simultaneous tests of millions of single nucleotide polymorphisms (SNP) for disease association. The SNPs in nearby genomic regions, however, are often highly correlated due to linkage disequilibrium (LD, a genetic term for correlation). Simple Bonferonni correction for multiple comparisons is therefore too conservative. Permutation tests, which are often employed in practice, are both computationally expensive for genome-wide studies and limite...
• Multivariate Matching Methods That Are Monotonic Imbalance Bounding AI翻译
  作者：Iacus, Stefano M.; King, Gary; Porro, Giuseppe
  作者单位：University of Milan; Harvard University; University of Trieste
  摘要：We introduce a new Monotonic Imbalance Bounding (MIB) class of matching methods for causal inference with a surprisingly large number of attractive statistical properties. MIB generalizes and extends in several new directions the only existing class, Equal Percent Bias Reducing (EPBR), which is designed to satisfy weaker properties and only in expectation. We also offer strategies to obtain specific members of the MIB class, and analyze in more detail a member of this class, called Coarsened E...