5期

最新文章

• ON THE EXISTENCE OF POWERFUL P-VALUES AND E-VALUES FOR COMPOSITE HYPOTHESES AI翻译
  作者：Zhang, Zhenyuan; Ramdas, Aaditya; Wang, Ruodu
  作者单位：Stanford University; Carnegie Mellon University; University of Waterloo
  摘要：Given a composite null P and composite alternative Q, when and how can we construct a p-value whose distribution is exactly uniform under the null, and stochastically smaller than uniform under the alternative? Similarly, when and how can we construct an e-value whose expectation exactly equals one under the null, but its expected logarithm under the alternative is positive? We answer these basic questions, and other related ones, when P and Q are convex polytopes (in the space of probability ...
• A NONPARAMETRIC TEST FOR ELLIPTICAL DISTRIBUTION BASED ON KERNEL EMBEDDING OF PROBABILITIES AI翻译
  作者：Tang, Yin; Li, Bing
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：Elliptical distribution is a basic assumption underlying many multivariate statistical methods. For example, in sufficient dimension reduction and statistical graphical models, this assumption is routinely imposed to simplify the data dependence structure. Before applying such methods, we need to decide whether the data are elliptically distributed. Currently existing tests either focus exclusively on spherical distributions, or rely on bootstrap to determine the null distribution, or require ...
• SIMULTANEOUS STATISTICAL INFERENCE FOR SECOND ORDER PARAMETERS OF TIME SERIES UNDER WEAK CONDITIONS AI翻译
  作者：Zhang, Yunyi; Paparoditis, Efstathios; Politis, Dimitris n.
  作者单位：The Chinese University of Hong Kong, Shenzhen; University of California System; University of California San Diego; University of California System; University of California San Diego
  摘要：Strict stationarity is an assumption commonly used in time-series analysis in order to derive asymptotic distributional results for second-order statistics, like sample autocovariances and sample autocorrelations. Focusing on weak stationarity, this paper derives the asymptotic distribution of the maximum of sample autocovariances and sample autocorrelations under weak conditions by using Gaussian approximation techniques. The asymptotic theory for parameter estimators obtained by fitting a (l...