2016

最新文章

• Detecting relevant changes in time series models AI翻译
  作者：Dette, Holger; Wied, Dominik
  作者单位：Ruhr University Bochum; Dortmund University of Technology
  摘要：Most of the literature on change point analysis by means of hypothesis testing considers hypotheses of the formH0 :theta(1=)theta(2) versus H-1 :theta(1)not equal theta(2) where theta(1) and theta(2) denote parameters of the process before and after a change point. The paper takes a different perspective and investigates the null hypotheses of no relevant changes, i. e. H-0 : parallel to theta(1) - theta(2)parallel to <=Delta, where parallel to parallel to is an appropriate norm. This formulat...
• Distance shrinkage and Euclidean embedding via regularized kernel estimation AI翻译
  作者：Zhang, Luwan; Wahba, Grace; Yuan, Ming
  作者单位：University of Wisconsin System; University of Wisconsin Madison
  摘要：Although recovering a Euclidean distance matrix from noisy observations is a common problem in practice, how well this could be done remains largely unknown. To fill in this void, we study a simple distance matrix estimate based on the so-called regularized kernel estimate. We show that such an estimate can be characterized as simply applying a constant amount of shrinkage to all observed pairwise distances. This fact allows us to establish risk bounds for the estimate, implying that the true ...
• Variable selection for support vector machines in moderately high dimensions AI翻译
  作者：Zhang, Xiang; Wu, Yichao; Wang, Lan; Li, Runze
  作者单位：North Carolina State University; University of Minnesota System; University of Minnesota Twin Cities; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：The support vector machine (SVM) is a powerful binary classification tool with high accuracy and great flexibility. It has achieved great success, but its performance can be seriously impaired if many redundant covariates are included. Some efforts have been devoted to studying variable selection for SVMs, but asymptotic properties, such as variable selection consistency, are largely unknown when the number of predictors diverges to 1. We establish a unified theory for a general class of non-c...
• Of quantiles and expectiles: consistent scoring functions, Choquet representations and forecast rankings AI翻译
  作者：Ehm, Werner; Gneiting, Tilmann; Jordan, Alexander; Krueger, Fabian
  作者单位：Heidelberg Institute for Theoretical Studies; Helmholtz Association; Karlsruhe Institute of Technology
  摘要：In the practice of point prediction, it is desirable that forecasters receive a directive in the form of a statistical functional. For example, forecasters might be asked to report the mean or a quantile of their predictive distributions. When evaluating and comparing competing forecasts, it is then critical that the scoring function used for these purposes be consistent for the functional at hand, in the sense that the expected score is minimized when following the directive. We show that any...
• Making a non-parametric density estimator more attractive, and more accurate, by data perturbation AI翻译
  作者：Doosti, Hassan; Hall, Peter
  作者单位：Mashhad University of Medical Sciences; University of Melbourne
  摘要：Motivated by both the shortcomings of high order density estimators, and the increasingly large data sets in many areas of modern science, we introduce new high order, non-parametric density estimators that are guaranteed to be positive and do not have highly oscillatory tails. Our approach is based on data perturbation, e.g. by tilting or data sharpening. It leads to new estimators that are more accurate than conventional kernel techniques that use positive kernels, but which nevertheless enj...
• Optimal designs for the prediction of individual parameters in hierarchical models AI翻译
  作者：Prus, Maryna; Schwabe, Rainer
  作者单位：Otto von Guericke University
  摘要：Characterizations of optimal designs are derived for the prediction of individual response curves within the framework of hierarchical linear mixed models. It is shown that the so-obtained optimal designs may differ substantially from those propagated in the literature so far and that the latter may become useless in terms of their performance.
• Tests for high dimensional generalized linear models AI翻译
  作者：Guo, Bin; Chen, Song Xi
  作者单位：Sichuan University; Peking University; Iowa State University
  摘要：We consider testing regression coefficients in high dimensional generalized linear models. By modifying the test statistic of Goeman and his colleagues for large but fixed dimensional settings, we propose a new test, based on an asymptotic analysis, that is applicable for diverging dimensions and is robust to accommodate a wide range of link functions. The power properties of the tests are evaluated asymptotically under two families of alternative hypotheses. In addition, a test in the presenc...
• Extensible grids: uniform sampling on a space filling curve AI翻译
  作者：He, Zhijian; Owen, Art B.
  作者单位：Tsinghua University; Stanford University
  摘要：We study the properties of points in [0,1]d generated by applying Hilbert's space filling curve to uniformly distributed points in [0,1]. For deterministic sampling we obtain a discrepancy of O(n-1/d) for d2. For random stratified sampling, and scrambled van der Corput points, we derive a mean-squared error of O(n-1-2/d) for integration of Lipschitz continuous integrands, when d3. These rates are the same as those obtained by sampling on d-dimensional grids and they show a deterioration with i...
• Drift estimation in sparse sequential dynamic imaging, with application to nanoscale fluorescence microscopy AI翻译
  作者：Hartmann, Alexander; Huckemann, Stephan; Dannemann, Joern; Laitenberger, Oskar; Geisler, Claudia; Egner, Alexander; Munk, Axel
  作者单位：University of Gottingen; Max Planck Society
  摘要：A major challenge in many modern superresolution fluorescence microscopy techniques at the nanoscale lies in the correct alignment of long sequences of sparse but spatially and temporally highly resolved images. This is caused by the temporal drift of the protein structure, e.g. due to temporal thermal inhomogeneity of the object of interest or its supporting area during the observation process. We develop a simple semiparametric model for drift correction in single-marker switching microscopy...
• On the coverage bound problem of empirical likelihood methods for time series AI翻译
  作者：Zhang, Xianyang; Shao, Xiaofeng
  作者单位：University of Missouri System; University of Missouri Columbia; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：The upper bounds on the coverage probabilities of the confidence regions based on blockwise empirical likelihood and non-standard expansive empirical likelihood methods for time series data are investigated via studying the probability of violating the convex hull constraint. The large sample bounds are derived on the basis of the pivotal limit of the blockwise empirical log-likelihood ratio obtained under fixed b asymptotics, which has recently been shown to provide a more accurate approximat...