Journal of the Royal Statistical Society: Series B

最新文章

• Identifying the latent space geometry of network models through analysis of curvature AI翻译
  作者：Lubold, Shane; Chandrasekhar, Arun G.; McCormick, Tyler H.
  作者单位：University of Washington; University of Washington Seattle; Stanford University; National Bureau of Economic Research; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
  摘要：A common approach to modelling networks assigns each node to a position on a low-dimensional manifold where distance is inversely proportional to connection likelihood. More positive manifold curvature encourages more and tighter communities; negative curvature induces repulsion. We consistently estimate manifold type, dimension, and curvature from simply connected, complete Riemannian manifolds of constant curvature. We represent the graph as a noisy distance matrix based on the ties between ...
• Peter J. Bickel, Derek Bean, Aiyou Chen and Purnamrita Sarkar's contribution to the Discussion of 'Vintage Factor Analysis with Varimax Performs Statistical Inference' by Rohe & Zeng AI翻译
  作者：Bickel, Peter J.; Bean, Derek; Chen, Aiyou; Sarkar, Purnamrita
  作者单位：University of Wisconsin System; University of Wisconsin Madison
• Autoregressive optimal transport models (May, qkad051, 2023) AI翻译
  作者：Zhu, Changbo; Muller, Hans-Georg
• Statistical testing under distributional shifts AI翻译
  作者：Thams, Nikolaj; Saengkyongam, Sorawit; Pfister, Niklas; Peters, Jonas
  作者单位：University of Copenhagen
  摘要：We introduce statistical testing under distributional shifts. We are interested in the hypothesis P*? H(0 )for a target distribution P*, but observe data from a different distribution Q*. We assume that P* is related to Q* through a known shift t and formally introduce hypothesis testing in this setting. We propose a general testing procedure that first resamples from the observed data to construct an auxiliary data set (similarly to sampling importance resampling) and then applies an existing...
• Joshua Cape's contribution to the Discussion of 'Vintage Factor Analysis with Varimax Performs Statistical Inference' by Rohe & Zeng AI翻译
  作者：Cape, Joshua
  作者单位：University of Wisconsin System; University of Wisconsin Madison
• Vintage factor analysis with Varimax performs statistical inference AI翻译
  作者：Wang, Tao
  作者单位：University of Victoria
• Strategic two-sample test via the two-armed bandit process AI翻译
  作者：Chen, Zengjing; Yan, Xiaodong; Zhang, Guodong
  作者单位：Shandong University; Shandong University; Shandong University
  摘要：This study aims to improve the power of two-sample tests by analysing whether the difference between two population parameters is larger than a prespecified positive equivalence margin. The classic test statistic treats the original data as exchangeable, while the proposed test statistic breaks the structure and proposes employing a two-armed bandit process to strategically integrate the data and thus a strategy-specific test statistic is constructed by combining the classic CLT with the law o...
• Autoregressive optimal transport models AI翻译
  作者：Zhu, Changbo; Mueller, Hans-Georg
  作者单位：University of Notre Dame; University of California System; University of California Davis
  摘要：Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the space of optimal transport maps. The autoregressive transport models that we introduce here are based on regressing optimal transport maps on each other, where predict...
• A kernel Stein test for comparing latent variable models AI翻译
  作者：Kanagawa, Heishiro; Jitkrittum, Wittawat; Mackey, Lester; Fukumizu, Kenji; Gretton, Arthur
  作者单位：University of London; University College London; Max Planck Society; Alphabet Inc.; Google Incorporated; Microsoft; Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan
  摘要：We propose a kernel-based nonparametric test of relative goodness of fit, where the goal is to compare two models, both of which may have unobserved latent variables, such that the marginal distribution of the observed variables is intractable. The proposed test generalizes the recently proposed kernel Stein discrepancy (KSD) tests (Liu et al., Proceedings of the 33rd international conference on machine learning (pp. 276-284); Chwialkowski et al., (2016), In Proceedings of the 33rd internation...
• The HulC: confidence regions from convex hulls AI翻译
  作者：Kuchibhotla, Arun Kumar; Balakrishnan, Sivaraman; Wasserman, Larry
  作者单位：Carnegie Mellon University; Carnegie Mellon University
  摘要：We develop and analyse the HulC, an intuitive and general method for constructing confidence sets using the convex hull of estimates constructed from subsets of the data. Unlike classical methods which are based on estimating the (limiting) distribution of an estimator, the HulC is often simpler to use and effectively bypasses this step. In comparison to the bootstrap, the HulC requires fewer regularity conditions and succeeds in many examples where the bootstrap provably fails. Unlike sub-sam...