1999

最新文章

• On estimation of monotone and concave frontier functions AI翻译
  作者：Gijbels, I; Mammen, E; Park, BU; Simar, L
  作者单位：Universite Catholique Louvain; Ruprecht Karls University Heidelberg; Seoul National University (SNU); Universite Catholique Louvain; Universite Catholique Louvain
  摘要：When analyzing the productivity of firms, one may want to compare how the firms transform a set of inputs I (typically labor, energy or capital) into an output y (typically a quantity of goods produced). The economic efficiency of a firm is then defined in terms of its ability to operate close to or on the production frontier, the boundary of the production set. The Frontier function gives the maximal level of output attainable by a firm for a given combination of its inputs. The efficiency of...
• Analyzing multiple emotions over time by autoregressive negative multinomial regression models AI翻译
  作者：Böckenholt, U
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
  摘要：This article presents an autoregressive random coefficient model with overdispersed negative multinomial marginal distributions for the analysis of heterogeneity and serial dependencies in multivariate longitudinal count data. The model structure consists of four components that take into account (a) individual difference effects, (b) random time effects, (c) multiple event categories, and (d) autodependencies. The last component is based on a stochastic integer-valued autoregressive process p...
• Combining data from polymerase chain reaction DNA typing experiments: Applications to sperm typing data AI翻译
  作者：Navidi, W; Arnheim, N
  作者单位：Colorado School of Mines; University of Southern California
  摘要：The polymerase chain reaction (PCR) is a procedure by which the DNA in a single cell can be made to replicate many times in a test tube. By amplifying the DNA from individual sperm cells and typing the results, estimates of male recombination fractions can be made, which are valuable for creating genetic maps and locating regions of unusually intense crossover activity on the human genome. Because PCR typing results are subject to random error, stochastic models must be constructed to obtain a...
• Variable selection and function estimation in additive nonparametric regression using a data-based prior - Comment AI翻译
  作者：MacEachern, SN; Shen, XT
  作者单位：University System of Ohio; Ohio State University
• 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
• Bridging different eras in sports - Comment AI翻译
  作者：Albert, J
  作者单位：University System of Ohio; Bowling Green 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...
• Detecting common signals in multiple time series using the spectral envelope AI翻译
  作者：Stoffer, DS
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：One often collects p individual time series Y-j(t) for j = 1,..., p, where the interest is to discover whether any-and which-of the series contain common signals. Let Y(t) = (Y-1(t),...,Y-p(t))' denote the corresponding p x 1 vector-valued time series with p x p positive definite spectral matrix f(Y)(w). Models are proposed to answer the primary question of which, if any, series have common Spectral power at approximately the same frequency. These models yield a type of complex factor analytic...