531期

最新文章

• Testing for Jump Spillovers Without Testing for Jumps AI翻译
  作者：Corradi, Valentina; Distaso, Walter; Fernandes, Marcelo
  作者单位：University of Surrey; Imperial College London; Getulio Vargas Foundation
  摘要：This article develops statistical tools for testing conditional independence among the jump components of the daily quadratic variation, which we estimate using intraday data. To avoid sequential bias distortion, we do not pretest for the presence of jumps. If the null is true, our test statistic based on daily integrated jumps weakly converges to a Gaussian random variable if both assets have jumps. If instead at least one asset has no jumps, then the statistic approaches zero in probability....
• Bayesian Model Search for Nonstationary Periodic Time Series AI翻译
  作者：Hadj-Amar, Beniamino; Rand, Barbel Finkenstadt; Fiecas, Mark; Levi, Francis; Huckstepp, Robert
  作者单位：University of Warwick; University of Minnesota System; University of Minnesota Twin Cities; University of Warwick; University of Warwick
  摘要：We propose a novel Bayesian methodology for analyzing nonstationary time series that exhibit oscillatory behavior. We approximate the time series using a piecewise oscillatory model with unknown periodicities, where our goal is to estimate the change-points while simultaneously identifying the potentially changing periodicities in the data. Our proposed methodology is based on a trans-dimensional Markov chain Monte Carlo algorithm that simultaneously updates the change-points and the periodici...
• GAP: A General Framework for Information Pooling in Two-Sample Sparse Inference AI翻译
  作者：Xia, Yin; Cai, T. Tony; Sun, Wenguang
  作者单位：Fudan University; University of Pennsylvania; University of Southern California
  摘要：This article develops a general framework for exploiting the sparsity information in two-sample multiple testing problems. We propose to first construct a covariate sequence, in addition to the usual primary test statistics, to capture the sparsity structure, and then incorporate the auxiliary covariates in inference via a three-step algorithm consisting of grouping, adjusting and pooling (GAP). The GAP procedure provides a simple and effective framework for information pooling. An important a...
• Efficiently Inferring the Demographic History of Many Populations With Allele Count Data AI翻译
  作者：Kamm, Jack; Terhorst, Jonathan; Durbin, Richard; Song, Yun S.
  作者单位：Wellcome Trust Sanger Institute; University of Cambridge; University of Michigan System; University of Michigan; University of California System; University of California Berkeley; University of California System; University of California Berkeley; Chan Zuckerberg Initiative (CZI)
  摘要：The sample frequency spectrum (SFS), or histogram of allele counts, is an important summary statistic in evolutionary biology, and is often used to infer the history of population size changes, migrations, and other demographic events affecting a set of populations. The expected multipopulation SFS under a given demographic model can be efficiently computed when the populations in the model are related by a tree, scaling to hundreds of populations. Admixture, back-migration, and introgression ...
• Modeling Between-Study Heterogeneity for Improved Replicability in Gene Signature Selection and Clinical Prediction AI翻译
  作者：Rashid, Nairn U.; Li, Quefeng; Yeh, Jen Jen; Ibrahim, Joseph G.
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill
  摘要：In the genomic era, the identification of gene signatures associated with disease is of significant interest. Such signatures are often used to predict clinical outcomes in new patients and aid clinical decision-making. However, recent studies have shown that gene signatures are often not replicable. This occurrence has practical implications regarding the generalizability and clinical applicability of such signatures. To improve replicability, we introduce a novel approach to select gene sign...
• Distance-Based Analysis of Ordinal Data and Ordinal Time Series AI翻译
  作者：Weiss, Christian H.
  作者单位：Helmut Schmidt University
  摘要：The dissimilarity of ordinal categories can be expressed with a distance measure. A unified approach relying on expected distances is proposed to obtain well-interpretable measures of location, dispersion, or symmetry of random variables, as well as measures of serial dependence within a given process. For special types of distance, these analytic tools lead to known approaches for ordinal or real-valued random variables. We also analyze the sample counterparts of the proposed measures and der...
• Simple Local Polynomial Density Estimators AI翻译
  作者：Cattaneo, Matias D.; Jansson, Michael; Ma, Xinwei
  作者单位：Princeton University; CREATES; University of California System; University of California Berkeley; University of California System; University of California San Diego
  摘要：This article introduces an intuitive and easy-to-implement nonparametric density estimator based on local polynomial techniques. The estimator is fully boundary adaptive and automatic, but does not require prebinning or any other transformation of the data. We study the main asymptotic properties of the estimator, and use these results to provide principled estimation, inference, and bandwidth selection methods. As a substantive application of our results, we develop a novel discontinuity in d...
• Principal Boundary on Riemannian Manifolds AI翻译
  作者：Yao, Zhigang; Zhang, Zhenyue
  作者单位：National University of Singapore; Zhejiang University
  摘要：We consider the classification problem and focus on nonlinear methods for classification on manifolds. For multivariate datasets lying on an embedded nonlinear Riemannian manifold within the higher-dimensional ambient space, we aim to acquire a classification boundary for the classes with labels, using the intrinsic metric on the manifolds. Motivated by finding an optimal boundary between the two classes, we invent a novel approach-the principal boundary. From the perspective of classification...
• Comparing and Weighting Imperfect Models Using D-Probabilities AI翻译
  作者：Li, Meng; Dunson, David B.
  作者单位：Rice University; Duke University
  摘要：We propose a new approach for assigning weights to models using a divergence-based method (D-probabilities), relying on evaluating parametric models relative to a nonparametric Bayesian reference using Kullback-Leibler divergence. D-probabilities are useful in goodness-of-fit assessments, in comparing imperfect models, and in providing model weights to be used in model aggregation. D-probabilities avoid some of the disadvantages of Bayesian model probabilities, such as large sensitivity to pri...
• Feature Selection by Canonical Correlation Search in High-Dimensional Multiresponse Models With Complex Group Structures AI翻译
  作者：Luo, Shan; Chen, Zehua
  作者单位：Shanghai Jiao Tong University; National University of Singapore
  摘要：High-dimensional multiresponse models with complex group structures in both the response variables and the covariates arise from current researches in important fields such as genetics and medicine. However, no enough research has been done on such models. One of a few researches, if not the only one, is the article by Li, Nan, and Zhu where the sparse group Lasso approach is extended to such models. In this article, we propose a novel approach named the sequential canonical correlation search...