2期

最新文章

• Kiefer ordering of simplex designs for second-degree mixture models with four or more ingredients AI翻译
  作者：Draper, NR; Heiligers, B; Pukelsheim, F
  作者单位：University of Wisconsin System; University of Wisconsin Madison; Otto von Guericke University; University of Augsburg
  摘要：For mixture models an the simplex, we discuss the improvement of a given design in terms of increasing symmetry, as well as obtaining a larger moment matrix under the Loewner ordering. The two criteria together define the Kiefer design ordering. For the second-degree mixture model, we show that the set of weighted centroid designs constitutes a convex complete class for the Kiefer ordering. For four ingredients, the class is minimal complete. Of essential importance for the derivation is a cer...
• Bayesian aspects of some nonparametric problems AI翻译
  作者：Zhao, LH
  作者单位：University of Pennsylvania
  摘要：We study the Bayesian approach to nonparametric function estimation problems such as nonparametric regression and signal estimation. We consider the asymptotic properties of Bayes procedures for conjugate (=Gaussian) priors. We show that so long as the prior puts nonzero measure on the very large parameter sat of interest then the Bayes estimators are not satisfactory. More specifically, we show that these estimators do not achieve the correct minim:ur rate over norm bounded sets in the parame...
• Optimal design with many blocking factors AI翻译
  作者：Morgan, JP; Bailey, RA
  作者单位：Old Dominion University; University of London; Queen Mary University London
  摘要：Designs for sets of experimental units with many blocking factors are studied. It is shown that if the set of blocking factors satisfies a certain simple condition then the information matrix for the design has a simple form. In consequence, a design is optimal if it is optimal with respect to one particular blocking factor and regular with respect to all the rest, in a sense which is made precise in the paper. This encompasses several previous results for optimal designs with more than one bl...
• Structural properties and convergence results for contours of sample statistical depth functions AI翻译
  作者：Zuo, YJ; Serfling, R
  作者单位：Arizona State University; Arizona State University-Tempe; University of Texas System; University of Texas Dallas
  摘要：Statistical depth functions have become increasingly used in nonparametric inference for multivariate data. Here the contours of such functions are studied. Structural properties of the regions enclosed by contours, such as affine equivariance, nestedness, connectedness and compactness, and almost sure convergence results for sample depth contours, are established. Also, specialized results are established for some popular depth functions, including halfspace depth, and for the case of ellipti...
• Additive logistic regression:: A statistical view of boosting -: Discussion AI翻译
  作者：Bühlmann, P; Yu, B
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich; University of California System; University of California Berkeley; AT&T; University of California System; University of California Berkeley
• Empirical geometry of multivariate data: A deconvolution approach AI翻译
  作者：Koltchinskii, VI
  作者单位：University of New Mexico
  摘要：Let {Y (j): j = 1,..., n} be independent observations in R-m, m greater than or equal to 1 with common distribution Q. Suppose that Y (j) = X (j) + xi (j), j = 1,...,n, where {X (j), xi (j), j = 1,...,n} are independent, X (j), j = 1,..., n have common distribution P and xi (j), j = 1,...,n have common distribution mu, so that Q = P * mu. The problem is to recover hidden geometric structure of the support of P based an the independent observations Y (j). Assuming that the distribution of the e...
• General notions of statistical depth function AI翻译
  作者：Zuo, YJ; Serfling, R
  作者单位：Arizona State University; Arizona State University-Tempe; University of Texas System; University of Texas Dallas
  摘要：Statistical depth Functions are being formulated ad hoc with increasing popularity in nonparametric inference for multivariate data. Here we introduce several general structures for depth functions, classify many existing examples as special cases, and establish results on the possession, or lack thereof, of four key properties desirable for depth functions in general. Roughly speaking, these properties may be described as: affine invariance, maximality at center, monotonicity relative to deep...
• Additive logistic regression: A statistical view of boosting AI翻译
  作者：Friedman, J; Hastie, T; Tibshirani, R
  作者单位：Stanford University; Stanford University; United States Department of Energy (DOE); SLAC National Accelerator Laboratory; Stanford University
  摘要：Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted Versions of the training data and then taking a weighted majority vote of the sequence of classifiers thus produced. For many classification algorithms, this simple strategy results in dramatic improvements in performance. We show that this seemingly mysterious phenomenon can be understood in terms of well-known statistical pr...
• Additive logistic regression: A statistical view of boosting - Discussion AI翻译
  作者：Ridgeway, G
  作者单位：University of Washington; University of Washington Seattle
• Convergence rates of posterior distributions AI翻译
  作者：Ghosal, S; Ghosh, JK; Van der Vaart, AW
  作者单位：Vrije Universiteit Amsterdam; Indian Statistical Institute; Indian Statistical Institute Kolkata
  摘要：We consider the asymptotic behavior of posterior distributions and Bayes estimators for infinite-dimensional statistical models. We give general results on the rate of convergence of the posterior measure. These are applied to several examples, including priors on finite sieves, log-spline models, Dirichlet processes and interval censoring.