Journal of the American Statistical Association

最新文章

• Rejoinder AI翻译
  作者：Benjamini, Y; Yekutieli, D
• Approximate and asymptotic distributions of chi-squared-type mixtures with applications AI翻译
  作者：Zhang, JT
  作者单位：National University of Singapore
  摘要：In this article we study how to approximate a random variable T of general chi-squared-type mixtures by a random variable of the form alpha chi(2)(d) + beta via matching the first three cumulants. The approximation error bounds for the density functions of the chi-squared approximation and the normal approximation are established. Applications of the results to some nonparametric goodness-of-fit tests, including those tests based on orthogonal series, smoothing splines, and local polynomial sm...
• Efficient empirical Bayes variable selection and estimation in linear models AI翻译
  作者：Yuan, M; Lin, Y
  作者单位：University System of Georgia; Georgia Institute of Technology; University of Wisconsin System; University of Wisconsin Madison
  摘要：We propose an empirical Bayes method for variable selection and coefficient estimation in linear regression models. The method is based on a particular hierarchical Bayes formulation, and the empirical Bayes estimator is shown to be closely related to the LASSO estimator. Such a connection allows us to take advantage of the recently developed quick LASSO algorithm to compute the empirical Bayes estimate, and provides a new way to select the tuning parameter in the LASSO method. Unlike previous...
• Measurement error in linear autoregressive models AI翻译
  作者：Staudenmayer, J; Buonaccorsi, JR
  作者单位：University of Massachusetts System; University of Massachusetts Amherst
  摘要：Time series data are often subject to measurement error, usually the result of needing to estimate the variable of interest. Although it is often reasonable to assume that the measurement error is additive (i.e., the estimator is conditionally unbiased for the missing true value), the measurement error variances often vary as a result of changes in the population/process over time and/or changes in sampling effort. In this article we address estimation of the parameters in linear autoregressiv...
• False discovery rate-adjusted multiple confidence intervals for selected parameters - Comment AI翻译
  作者：Edwards, D
  作者单位：University of South Carolina System; University of South Carolina Columbia
• Robust estimation in generalized partial linear models for clustered data AI翻译
  作者：He, XM; Fung, WK; Zhu, ZY
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Hong Kong; East China Normal University
  摘要：In this article we consider robust generalized estimating equations for the analysis of semiparametric generalized partial linear models (GPLMs) for longitudinal data or clustered data in general. We approximate the nonparametric function in the GPLM by a regression spline, and use bounded scores and leverage-based weights in the estimating equation to achieve robustness against outliers. We show that the regression spline approach avoids some of the intricacies associated with the profile-ker...
• Untitled AI翻译
  作者：Louis, TA
  作者单位：Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health
• Bayesians, frequentists, and scientists AI翻译
  作者：Efron, B
  作者单位：Stanford University
  摘要：Broadly speaking, nineteenth century statistics was Bayesian, while the twentieth century was frequentist, at least from the point of view of most scientific practitioners. Here in the twenty-first century scientists are bringing statisticians much bigger problems to solve, often comprising millions of data points and thousands of parameters. Which statistical philosophy will dominate practice? My guess, backed up with some recent examples, is that a combination of Bayesian and frequentist ide...
• Semilinear high-dimensional model for normalization of microarray data: A theoretical analysis and partial consistency AI翻译
  作者：Fan, JQ; Peng, H; Huang, T
  作者单位：Princeton University; Yale University
  摘要：Normalization of microarray data is essential for removing experimental biases and revealing meaningful biological results. Motivated by a problem of normalizing microarray data, a semilinear in-slide model (SLIM) has been proposed. To aggregate information from other arrays. SLIM is generalized to account for across-array information, resulting in an even more dynamic semiparametric regression model. This model can be used to normalize microarray data even when there is no replication within ...
• A unified nonparametric approach for unbalanced factorial designs AI翻译
  作者：Gao, X; Alvo, M
  作者单位：York University - Canada; University of Ottawa
  摘要：Motivated by questions arising from the field of statistical genetics, we consider the problem of testing main, nested, and interaction effects in unbalanced factorial designs. Based on the concept of composite linear rank statistics, a new notion of weighted rank is proposed. Asymptotic normality of weighted linear rank statistics is established under mild conditions, and consistent estimators are developed for the corresponding limiting covariance structure. A unified framework to use weight...