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• Gibbs flow for approximate transport with applications to Bayesian computation AI翻译
  作者：Heng, Jeremy; Doucet, Arnaud; Pokern, Yvo
  作者单位：ESSEC Business School; University of Oxford; University of London; University College London
  摘要：Let pi(0) and pi(1) be two distributions on the Borel space (R-d,B(R-d)). Any measurable function T:R-d -> R-d such that Y=T(X)similar to pi 1 if X similar to pi(0) is called a transport map from pi 0 to pi 1. For any pi 0 and pi(1), if one could obtain an analytical expression for a transport map from pi 0 to pi 1, then this could be straightforwardly applied to sample from any distribution. One would map draws from an easy-to-sample distribution pi(0) to the target distribution pi(1) using t...
• Optimal control of false discovery criteria in the two-group model AI翻译
  作者：Heller, Ruth; Rosset, Saharon
  作者单位：Tel Aviv University
  摘要：The highly influential two-group model in testing a large number of statistical hypotheses assumes that the test statistics are drawn independently from a mixture of a high probability null distribution and a low probability alternative. Optimal control of the marginal false discovery rate (mFDR), in the sense that it provides maximal power (expected true discoveries) subject to mFDR control, is known to be achieved by thresholding the local false discovery rate (locFDR), the probability of th...
• Use of model reparametrization to improve variational Bayes† AI翻译
  作者：Tan, Linda S. L.
  作者单位：National University of Singapore
  摘要：We propose using model reparametrization to improve variational Bayes inference for hierarchical models whose variables can be classified as global (shared across observations) or local (observation-specific). Posterior dependence between local and global variables is minimized by applying an invertible affine transformation on the local variables. The functional form of this transformation is deduced by approximating the posterior distribution of each local variable conditional on the global ...
• Smoothing splines on Riemannian manifolds, with applications to 3D shape space AI翻译
  作者：Kim, Kwang-Rae; Dryden, Ian L.; Le, Huiling; Severn, Katie E.
  作者单位：University of Nottingham
  摘要：There has been increasing interest in statistical analysis of data lying in manifolds. This paper generalizes a smoothing spline fitting method to Riemannian manifold data based on the technique of unrolling, unwrapping and wrapping originally proposed by Jupp and Kent for spherical data. In particular, we develop such a fitting procedure for shapes of configurations in general m-dimensional Euclidean space, extending our previous work for two-dimensional shapes. We show that parallel transpor...
• Report of the Editors-2020 AI翻译
  作者：Delaigle, Aurore; Wood, Simon
• Small area estimation with linked data AI翻译
  作者：Salvati, N.; Fabrizi, E.; Ranalli, M. G.; Chambers, R. L.
  作者单位：University of Pisa; Catholic University of the Sacred Heart; University of Perugia; University of Wollongong
  摘要：Data linkage can be used to combine values of the variable of interest from a national survey with values of auxiliary variables obtained from another source, such as a population register, for use in small area estimation. However, linkage errors can induce bias when fitting regression models; moreover, they can create non-representative outliers in the linked data in addition to the presence of potential representative outliers. In this paper, we adopt a secondary analyst's point of view, as...
• Construction of blocked factorial designs to estimate main effects and selected two-factor interactions AI翻译
  作者：Godolphin, J. D.
  作者单位：University of Surrey
  摘要：Two-level factorial designs are widely used in industry. For experiments involving n factors, the construction of designs comprising 2n and 2n-p factorials, arranged in blocks of size 2q is investigated. The aim is to estimate all main effects and a selected subset of two-factor interactions. Designs constructed according to minimum aberration criteria are shown to not necessarily be the most appropriate designs in this situation. A design construction approach is proposed which exploits known...
• The proximal Robbins-Monro method AI翻译
  作者：Toulis, Panos; Horel, Thibaut; Airoldi, Edoardo M.
  作者单位：University of Chicago; Harvard University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：The need for statistical estimation with large data sets has reinvigorated interest in iterative procedures and stochastic optimization. Stochastic approximations are at the forefront of this recent development as they yield procedures that are simple, general and fast. However, standard stochastic approximations are often numerically unstable. Deterministic optimization, in contrast, increasingly uses proximal updates to achieve numerical stability in a principled manner. A theoretical gap ha...
• Statistical inferences of linear forms for noisy matrix completion AI翻译
  作者：Xia, Dong; Yuan, Ming
  作者单位：Hong Kong University of Science & Technology; Columbia University
  摘要：We introduce a flexible framework for making inferences about general linear forms of a large matrix based on noisy observations of a subset of its entries. In particular, under mild regularity conditions, we develop a universal procedure to construct asymptotically normal estimators of its linear forms through double-sample debiasing and low-rank projection whenever an entry-wise consistent estimator of the matrix is available. These estimators allow us to subsequently construct confidence in...