446期

最新文章

• Prediction intervals, factor analysis models, and high-dimensional empirical linear prediction AI翻译
  作者：Ding, AA; Hwang, JTG
  作者单位：Northeastern University; Cornell University
  摘要：We discuss a technique that provides prediction intervals based on a model called an empirical linear model. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. In fact, a special case of the empirical model is the factor analysis model. A factor analysis model does not generally aim at prediction, however. Therefore, HELP can be viewed as a technique that provides prediction (and confidence) intervals ...
• Iterated transformation-kernel density estimation AI翻译
  作者：Yang, LJ; Marron, JS
  作者单位：Michigan State University; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Transformation from a parametric family can improve the performance of kernel density estimation. In this article we give two data-driven estimators for the optimal transformation parameter. We demonstrate that multiple families of transformations can be used at the same time, and there can be benefits to iterating this process. The transformation scheme can be expected to first pick the right transformation family and then pick the optimal parameter. Insight as to the performance of the metho...
• Self-consistency and principal component analysis AI翻译
  作者：Tarpey, T
  作者单位：University System of Ohio; Wright State University Dayton
  摘要：I examine the self-consistency of a principal component axis; that is, when a distribution is centered about a principal component axis. A principal component axis of a random vector X is self-consistent if each point on the axis corresponds to the mean of X given that X projects orthogonally onto that point. A large class of symmetric multivariate distributions are examined in terms of self-consistency of principal component subspaces. Elliptical distributions are characterized by the preserv...
• A model for evaluating sensitivity and specificity for correlated diagnostic tests in efficacy studies with an imperfect reference test (vol 93, pg 920, 1998) AI翻译
  作者：Qu, Y; Hadgu, A
  作者单位：Cleveland Clinic Foundation; Centers for Disease Control & Prevention - USA
• A conditional saddlepoint approximation for testing problems AI翻译
  作者：Gatto, R; Jammalamadaka, SR
  作者单位：ESSEC Business School; University of California System; University of California Santa Barbara
  摘要：A saddlepoint approximation is provided for the distribution function of one M statistic conditional on another M statistic. Many interesting statistics based on dependent quantities (e.g., spacings, multinomial frequencies, rank differences) can be expressed in terms of independent identically distributed random variables conditioned on their sum, so that this conditional saddlepoint approximation yields accurate approximations for the distribution of such statistics. This saddlepoint approxi...
• The best test of exponentiality against singly truncated normal alternatives AI翻译
  作者：del Castillo, J; Puig, P
  作者单位：Autonomous University of Barcelona
  摘要：we show that the likelihood ratio test of exponentiality against singly truncated normal alternatives is the uniformly most powerful unbiased test and can be expressed in terms of the sampling coefficient of variation. This test is closely related to Greenwood's statistic for testing departures from the uniform distribution. We provide a way to approximate the critical points of the test, using saddlepoint methods, that gives a high degree of accuracy.
• Regression depth - Comment AI翻译
  作者：Carroll, RJ; Ruppert, D; Stefanski, LA
  作者单位：Texas A&M University System; Texas A&M University College Station; Texas A&M University System; Texas A&M University College Station; Cornell University; North Carolina State University
• Bayesian morphology: Fast unsupervised Bayesian image analysis AI翻译
  作者：Forbes, F; Raftery, AE
  作者单位：University of Washington; University of Washington Seattle
  摘要：We consider the problems of image segmentation and classification, and image restoration when the true image is made up of a small number of (unordered) colors. Our emphasis is on both performance and speed; speed has become increasingly important for analyzing large images and multispectral images with many bands, processing large image databases, real-time or near realtime image analysis, and the online analysis of video. Bayesian image analysis provides an elegant solution to these problems...
• Comment on Stute, Manteiga, and Quindimil AI翻译
  作者：Wilcox, RR
  作者单位：University of Southern California
• Extensions of calibration estimators in survey sampling AI翻译
  作者：Théberge, A
  作者单位：Statistics Canada
  摘要：Estimators from the family of calibration estimators are often used when auxiliary information about a population is available. By viewing calibration as an algebraic problem, this article extends the: calibration technique to estimate population parameters other than totals and means, and also extends the technique to the case where there is no solution to the calibration equation. These extensions permit the development of estimators for small domains that have a synthetic component and yet ...