Journal of the American Statistical Association

最新文章

• NERVE-CELL SPIKE TRAIN DATA-ANALYSIS - A PROGRESSION OF TECHNIQUE AI翻译
  作者：BRILLINGER, DR
  摘要：Collections of occurrence times of events taking place irregularly in time provide a fairly common, but not broadly discussed, data type. This article is concerned with the particular circumstance of firing times in nerve cells that interact and form networks. The article reviews a progression of statistical analysis techniques: description, association as measured by moments and correlation, regression, and finally likelihood. The data is point process, but may be seen as that of regression a...
• DIAGNOSTICS FOR NONPARAMETRIC REGRESSION-MODELS WITH ADDITIVE TERMS AI翻译
  作者：GU, C
  作者单位：University of British Columbia
  摘要：Recent developments of multivariate smoothing methods provide a rich collection of feasible models for nonparametric multivariate data analysis. Among the most interpretable are models with additive terms. Construction of various models and algorithms for computing the models have been the main concern of the existing literature in this area. Few results are available on the validation of computed fits, and many applications of nonparametric methods unfortunately end up interpreting the noise....
• A TEST FOR EXTREME VALUE DOMAIN OF ATTRACTION AI翻译
  作者：HASOFER, AM; WANG, Z
  摘要：A simple statistic is proposed to test the hypothesis that a sample comes from a distribution in the domain of attraction of the Gumbel distribution. It is based on the top k order statistics and is a generalization of the Shapiro-Wilk goodness-of-fit statistic. The critical region of the test and its power against the alterative that the sample comes from a distribution in another domain of attraction are studied theoretically and by simulation. The power turns out to be superior to that of o...
• 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...
• POWER CALCULATIONS FOR GENERAL LINEAR MULTIVARIATE MODELS INCLUDING REPEATED MEASURES APPLICATIONS AI翻译
  作者：MULLER, KE; LAVANGE, LM; RAMEY, SL; RAMEY, CT
  作者单位：Research Triangle Institute; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina; University of North Carolina Chapel Hill; University of Alabama System; University of Alabama Birmingham
  摘要：Recently developed methods for power analysis expand the options available for study design. We demonstrate methods can be applied by (1) reviewing their formulation and (2) describing their application in the preparation of a particular grant proposal. The focus is a complex but ubiquitous setting: repeated measures in a longitudinal study. Describing the development of the research proposal allows demonstrating the steps needed to conduct an effective power analysis. Discussion of the exampl...
• STATISTICAL ISSUES ARISING IN AIDS CLINICAL-TRIALS - REJOINDER AI翻译
  作者：ELLENBERG, SS; FINKELSTEIN, DM; SCHOENFELD, DA
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard Medical School
• DESIGNING EXPERIMENTS AND ANALYZING DATA - A MODEL COMPARISON PERSPECTIVE - COMMENT AI翻译
  作者：BRODY, J
• 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...
• BANDWIDTH CHOICE FOR AVERAGE DERIVATIVE ESTIMATION AI翻译
  作者：HARDLE, W; HART, J; MARRON, JS; TSYBAKOV, AB
  作者单位：Texas A&M University System; Texas A&M University College Station; University of North Carolina; University of North Carolina Chapel Hill; Russian Academy of Sciences
  摘要：The average derivative is the expected value of the derivative of a regression function. Kernel methods have been proposed as a means of estimating this quantity. The problem of bandwidth selection for these kernel estimators is addressed here. Asymptotic representations are found for the variance and squared bias. These are compared with each other to find an insightful representation for a bandwidth optimizing terms of lower order than n-1. It is interesting that, for dimensions greater than...
• PREAVERAGED LOCALIZED ORTHOGONAL POLYNOMIAL ESTIMATORS FOR SURFACE SMOOTHING AND PARTIAL DIFFERENTIATION AI翻译
  作者：AZARI, AS; MULLER, HG
  摘要：We propose a multivariate smoothing method based on products of localized orthogonal polynomial series estimators for a smooth regression surface in the fixed-design regression model. The estimation of partial derivatives is included. The proposed method provides for automatic and efficient boundary modifications near the edges of the surface, assuming that the boundary of the support of the regression function satisfies some regularity conditions. By allowing for a preaveraging step, the corr...