4期

最新文章

• Column-orthogonal strong orthogonal arrays of strength two plus and three minus AI翻译
  作者：Zhou, Yongdao; Tang, Boxin
  作者单位：Nankai University; Simon Fraser University
  摘要：Strong orthogonal arrays have better space-filling properties than ordinary orthogonal arrays for computer experiments. We consider column-orthogonal strong orthogonal arrays of strength two plus and three minus, and present methods of constructing such designs. Several situations are examined, including those of four or higher levels and mixed levels. The methods are based on both regular and nonregular designs. The resulting designs inherit the good property of strong orthogonal arrays of st...
• Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing AI翻译
  作者：Goeman, Jelle; Meijer, Rosa; Krebs, Thijmen; Solari, Aldo
  作者单位：Leiden University - Excl LUMC; Leiden University; Leiden University Medical Center (LUMC); Parnassia Psychiatric Institute; Delft University of Technology; University of Milano-Bicocca
  摘要：Closed testing procedures are classically used for familywise error rate control, but they can also be used to obtain simultaneous confidence bounds for the false discovery proportion in all subsets of the hypotheses, allowing for inference robust to post hoc selection of subsets. In this paper we investigate the special case of closed testing with Simes local tests. We construct a novel fast and exact shortcut and use it to investigate the power of this approach when the number of hypotheses ...
• Accounting for unobserved covariates with varying degrees of estimability in high-dimensional biological data AI翻译
  作者：McKennan, Chris; Nicolae, Dan
  作者单位：University of Chicago
  摘要：An important phenomenon in high-throughput biological data is the presence of unobserved covariates that can have a significant impact on the measured response. When these covariates are also correlated with the covariate of interest, ignoring or improperly estimating them can lead to inaccurate estimates of and spurious inference on the corresponding coefficients of interest in a multivariate linear model. We first prove that existing methods to account for these unobserved covariates often i...
• Sequentially additive nonignorable missing data modelling using auxiliary marginal information AI翻译
  作者：Sadinle, Mauricio; Reiter, Jerome P.
  作者单位：University of Washington; University of Washington Seattle; Duke University
  摘要：We study a class of missingness mechanisms, referred to as sequentially additive nonignorable, for modelling multivariate data with item nonresponse. These mechanisms explicitly allow the probability of nonresponse for each variable to depend on the value of that variable, thereby representing nonignorable missingness mechanisms. These missing data models are identified by making use of auxiliary information on marginal distributions, such as marginal probabilities for multivariate categorical...
• Bayesian jackknife empirical likelihood AI翻译
  作者：Cheng, Y.; Zhao, Y.
  作者单位：University System of Georgia; Georgia State University; University System of Georgia; Georgia State University
  摘要：Empirical likelihood is a very powerful nonparametric tool that does not require any distributional assumptions. Lazar (2003) showed that in Bayesian inference, if one replaces the usual likelihood with the empirical likelihood, then posterior inference is still valid when the functional of interest is a smooth function of the posterior mean. However, it is not clear whether similar conclusions can be obtained for parameters defined in terms of U-statistics. We propose the so-called Bayesian j...
• Testing for arbitrary interference on experimentation platforms AI翻译
  作者：Pouget-Abadie, J.; Saint-Jacques, G.; Saveski, M.; Duan, W.; Ghosh, S.; Xu, Y.; Airoldi, E. M.
  作者单位：Alphabet Inc.; Google Incorporated; Massachusetts Institute of Technology (MIT); Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Experimentation platforms are essential to large modern technology companies, as they are used to carry out many randomized experiments daily. The classic assumption of no interference among users, under which the outcome for one user does not depend on the treatment assigned to other users, is rarely tenable on such platforms. Here, we introduce an experimental design strategy for testing whether this assumption holds. Our approach is in the spirit of the Durbin-Wu-Hausman test for endogeneit...
• Bootstrapping spectral statistics in high dimensions AI翻译
  作者：Lopes, Miles E.; Blandino, Andrew; Aue, Alexander
  作者单位：University of California System; University of California Davis
  摘要：Statistics derived from the eigenvalues of sample covariance matrices are called spectral statistics, and they play a central role in multivariate testing. Although bootstrap methods are an established approach to approximating the laws of spectral statistics in low-dimensional problems, such methods are relatively unexplored in the high-dimensional setting. The aim of this article is to focus on linear spectral statistics as a class of prototypes for developing a new bootstrap in high dimensi...
• Conjugate Bayes for probit regression via unified skew-normal distributions AI翻译
  作者：Durante, Daniele
  作者单位：Bocconi University
  摘要：Regression models for dichotomous data are ubiquitous in statistics. Besides being useful for inference on binary responses, these methods serve as building blocks in more complex formulations, such as density regression, nonparametric classification and graphical models. Within the Bayesian framework, inference proceeds by updating the priors for the coefficients, typically taken to be Gaussians, with the likelihood induced by probit or logit regressions for the responses. In this updating, t...