419期

最新文章

• HIERARCHICAL BAYES MODELS FOR THE PROGRESSION OF HIV-INFECTION USING LONGITUDINAL CD4 T-CELL NUMBERS AI翻译
  作者：LANGE, N; CARLIN, BP; GELFAND, AE
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Connecticut
  摘要：Taking the absolute number of CD4 T-cells as a marker of disease progression for persons infected with the human immunodeficiency virus (HIV), we model longitudinal series of such counts for a sample of 327 subjects in the san Francisco Men's Health Study (Waves 1-8, excluding zidovudine cases). We conduct a fully Bayesian analysis of these data. We employ individual level nonlinear models incorporating such critical features as incomplete and unbalanced data, population covariates (age at stu...
• ARMA COVARIANCE-STRUCTURES WITH TIME HETEROSCEDASTICITY FOR REPEATED MEASURES EXPERIMENTS AI翻译
  作者：ROCHON, J
  作者单位：Western University (University of Western Ontario); University Western Ontario Hospital
  摘要：Rochon and Helms (1989) presented a model for analyzing repeated measures experiments. The general linear model was used to assess the influence of covariate information, and ARMA time series models were put forward to characterize the covariance matrix among the repeated measures. Practical experience has suggested, however, that the ARMA assumption of constant variances and autocovariances over time is too restrictive for many applications. For example, observations may be relatively stable ...
• EXISTENCE AND UNIQUENESS OF THE MAXIMUM-LIKELIHOOD ESTIMATOR FOR A MULTIVARIATE PROBIT MODEL AI翻译
  作者：LESAFFRE, E; KAUFMANN, H
  摘要：The multivariate probit model (MPM) is a particular case of the class of correlated prediction models. A correlated prediction mode is especially useful when prediction or classification is envisaged into diagnostic classes that are combinations of binary responses. The parameter vector consists of a location part and an association part. The location part accounts for the effect the regressors have on the marginal probabilities of the binary responses. The association part corrects these prob...
• ADAPTIVE BAYESIAN CLASSIFICATION OF SPATIAL DATA AI翻译
  作者：KLEIN, R; PRESS, SJ
  作者单位：University of California System; University of California Riverside
  摘要：A two-dimensional scene is analyzed statistically by superimposing on it a rectangular grid and studying each square picture element (pixel) as one unit of the entire picture. With each pixel we want to associate one of K labels, but the label must be determined. Labels may be related to one another spatially, reflecting an underlying pattern in the scene. There is a noisy observation vector associated with each pixel, and these vectors are used contextually to classify the pixels; that is, to...
• ESTIMATION OF WITHIN MODEL PARAMETERS IN REGRESSION-MODELS WITH A NESTED ERROR STRUCTURE AI翻译
  作者：WEERAKKODY, GJ; JOHNSON, DE
  作者单位：Kansas State University
  摘要：Restricted randomizations, similar to those in split-plot type experiments, often are adapted to assign quantitative treatment factors to experimental units. Such restrictions result in the experiment having a nested error structure. Sufficient conditions are presented under which ordinary least squares (OLS) estimates of regressor parameters are uniformly minimum variance unbiased (UMVU). If one designs experiments so that these conditions are satisfied, the analysis is straightforward and ea...
• THE BAYES NONBAYES COMPROMISE - A BRIEF REVIEW AI翻译
  作者：GOOD, IJ
  摘要：Various compromises that have occurred between Bayesian and non-Bayesian methods are reviewed. (A citation is provided that discusses the inevitability of compromises within the Bayesian approach.) One example deals with the masses of elementary particles, but no knowledge of physics will be assumed.
• A GENERALIZABLE FORMULATION OF CONDITIONAL LOGIT WITH DIAGNOSTICS AI翻译
  作者：SOOFI, ES
  摘要：The conditional logit model is a multinomial logit model that permits the inclusion of choice-specific attributes. This article shows that the conditional logit model will maximize entropy given a set of attribute-value preserving constraints. A correspondence between the maximum entropy (ME) and maximum likelihood (ML) estimates for logit probabilities is established. Some easily computable and useful diagnostics for logit analysis are provided, and it is shown that an evaluation of the relat...
• A TECHNIQUE FOR ESTIMATING MARGINAL POSTERIOR DENSITIES IN HIERARCHICAL-MODELS USING MIXTURES OF CONDITIONAL DENSITIES AI翻译
  作者：JOHNSON, VE
  摘要：A technique called quantile integration is proposed for the estimation of marginal posterior densities arising in Bayesian models having hierarchical representations. The method is based on approximating marginal densities as mixtures of conditional densities, where the conditioning variables are selected deterministically from the mixing distributions. The form of the approximation makes it easy to implement, and the resulting approximations are computationally efficient to obtain. The techni...