435期

最新文章

• Bootstrap selection of the smoothing parameter in nonparametric hazard bate estimation AI翻译
  作者：GonzalezManteiga, W; Cao, R; Marron, JS
  作者单位：Universidade da Coruna; University of North Carolina; University of North Carolina Chapel Hill
  摘要：An asymptotic representation of the mean weighted integrated squared error for the kernel-based estimator of the hazard rate in the presence of right-censored samples is obtained for different bootstrap resampling methods. As a consequence, a new bandwidth selector based on the bootstrap is introduced. Very satisfactory simulations results are obtained in comparison to the cross-validation selector for different models, using WARPed (i.e., binned) versions of the estimators.
• The selection of prior distributions by formal rules AI翻译
  作者：Kass, RE; Wasserman, L
  摘要：Subjectivism has become the dominant philosophical foundation for Bayesian inference. Yet in practice, most Bayesian analyses are performed with so-called ''noninformative'' priors, that is, priors constructed by some formal rule. We review the plethora of techniques for constructing such priors and discuss some of the practical and philosophical issues that arise when they are used. We give special emphasis to Jeffreys's rules and discuss the evolution of his viewpoint about the interpretatio...
• Testing for serial correlation against an ARMA(1, 1) process AI翻译
  作者：Andrews, DWK; Ploberger, W
  作者单位：University of St Andrews
  摘要：This article is concerned with tests for serial correlation in time series and in the errors of regression models. In particular, the nonstandard problem of testing for white noise against autoregressive moving average model ARMA(1, 1) alternatives is considered. The likelihood ratio (LR), sup Lagrange multiplier (LM), and exponential average LM and LR tests are shown to be asymptotically admissible for ARMA(1, 1) alternatives. In addition, they are shown to be consistent against all (weakly s...
• Permutation distributions via generating functions with applications to sensitivity analysis of discrete data AI翻译
  作者：Baglivo, J; Pagano, M; Spino, C
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health
  摘要：Generating functions provide a simple and elegant way to describe probability or frequency distributions of discrete statistics and, in particular, permutation distributions. They are also a computational tool. Many efficient algorithms, including those described as fast Fourier transform methods, network methods, and multiple shift methods, are different implementations of the recursions needed to evaluate generating functions efficiently. Our goals here are twofold. First, we make the relati...
• Improved pivotal methods for constructing confidence regions with directional data AI翻译
  作者：Hall, P; Jing, BY; Wood, ATA
  作者单位：Australian National University; Hong Kong University of Science & Technology; University of Bath
  摘要：The importance of pivoting is well established in the context of nonparametric confidence regions. It ensures enhanced coverage accuracy. However, pivoting for directional data cannot be achieved simply by rescaling. A somewhat cumbersome pivotal method, which involves passing first into a space of higher dimension, has been developed by Fisher and Hall for samples of unit vectors. Although that method has some advantages over nonpivotal techniques, it does suffer from certain drawbacks-in par...
• Identification of outliers in multivariate data AI翻译
  作者：Rocke, DM; Woodruff, DL
  摘要：New insights are given into why the problem of detecting multivariate outliers can be difficult and why the difficulty increases with the dimension of the data. Significant improvements in methods for detecting outliers are described, and extensive simulation experiments demonstrate that a hybrid method extends the practical boundaries of outlier detection capabilities. Based on simulation results and examples from the literature, the question of what levels of contamination can be detected by...
• Fitting full-information item factor models and an empirical investigation of bridge sampling AI翻译
  作者：Meng, XL; Schilling, S
  作者单位：Vanderbilt University
  摘要：Based on item response theory, Beck and Aitken introduced a method of item factor analysis, termed full-information item factor (FIIF) analysis by Bartholomew because it uses all distinct item response vectors as data. But a limitation of their fitting algorithm is its reliance on fixed-point Gauss-Hermite quadrature, which can produce appreciable numerical errors, especially in high-dimension problems. The first purpose of this article is to offer more reliable methods by using recent advance...
• A smooth nonparametric estimate of a mixing distribution using mixtures of Gaussians AI翻译
  作者：Magder, LS; Zeger, SL
  作者单位：Johns Hopkins University
  摘要：We propose a method of estimating mixing distributions using maximum likelihood over the class of arbitrary mixtures of Gaussians subject to the constraint that the component variances be greater than or equal to some minimum value h. This approach can lead to estimates of many shapes, with smoothness controlled by parameter h. We show that the resulting estimate will always be a finite mixture of Gaussians, each having variance h. The nonparametric maximum likelihood estimate can be viewed as...
• The equivalence of constrained and weighted designs in multiple objective design problems AI翻译
  作者：Clyde, M; Chaloner, K
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：Several competing objectives may be relevant in the design of an experiment. The competing objectives may not be easy to characterize in a single optimality criterion. One approach to these design problems has been to weight each criterion and find the design that optimizes the weighted average of the criteria. An alternative approach has been to optimize one criterion subject to constraints on the other criteria. An equivalence theorem is presented for the Bayesian constrained design problem....