一种基于椭圆曲线的部分盲签名方案

椭圆曲线数字签名实际上是基于乘法群的离散对数的数字签名在椭圆曲线上的模拟。本文讨论了部分盲签名的概念,并提出了两个基于椭圆曲线的部分盲签名方案,即单密钥部分盲签名方案和双密钥部分盲签名方案。该方案主要用于提高离线电子系统的效率和需要较短密钥的应用产品。     

商务本《古代汉语》通假字注释例商

郭锡良等人主编的1999年商务版《古代汉语》经过修订,补正了一些以往的注释疏误,质量得到了进一步的提高,但是该书在通假字注释方面仍存在一些不足。以列举的方式具体分析了书中将同义词、古今字、假借字等误作通假字及本借字互倒的情况,认为其有进一步补正和完善之必要。     

关于参数化测度（Ⅱ）

引进一类拓扑向量空间，用以描述测度的偏导。使用的工具是所谓的参数化鞅。建立了若干参数化鞅的收敛定理。     

De minimis and equity in risk

Indices and orderings are developed for evaluating alternative strategies in the management of risk. They reflect the goals of reducing individual and collective risks, of increasing equity, and of assigning priority to the reduction and to the equity of high risks. Individual risk is defined as the (random or non-random) level of exposure to a danger. In particular the role of a lower negligibility level is investigated. A class of indices is proposed which involves two parameters, a negligibility level and a parameter of inequality aversion, and several interpretations of the indices are discussed. We provide a set of eight axioms which are necessary and sufficient for this class of indices, and we present an approach to deal with partial information on the parameters.     

基于GRPLS 回归的 中国经济增长影响因素分析

构造一种新的方法———岭- 偏最小二乘回归方法(它既有效消除了因素变量之间的多 重共线性,又克服了传统方法的不足,且使模型更加稳健,具有更强的预测和分析能力) ;并运 用广义岭- 偏最小二乘回归方法分析了我国经济增长的影响因素,为我国制订持续、快速增长 的经济政策提供了有益的参考.     

A method for choosing the smoothing parameter in a semi-parametric model for detecting change-points in blood flow

In a smoothing spline model with unknown change-points, the choice of the smoothing parameter strongly influences the estimation of the change-point locations and the function at the change-points. In a tumor biology example, where change-points in blood flow in response to treatment were of interest, choosing the smoothing parameter based on minimizing generalized cross-validation (GCV) gave unsatisfactory estimates of the change-points. We propose a new method, aGCV, that re-weights the residual sum of squares and generalized degrees of freedom terms from GCV. The weight is chosen to maximize the decrease in the generalized degrees of freedom as a function of the weight value, while simultaneously minimizing aGCV as a function of the smoothing parameter and the change-points. Compared with GCV, simulation studies suggest that the aGCV method yields improved estimates of the change-point and the value of the function at the change-point.     

基于语料库的very，rather及quite在口语中与形容词的搭配研究

通过对BNC和SWECCL两个语料库中的口语语料进行检索，计算出与very，rather及quite搭配的形容词的MI值，并进行对比分析。分析结果表明，本族语者与中国英语专业学生在口语表达时都偏向于使用very，其次为quite，最后为rather；而中国英语专业学生在口语表达时过度使用very，对同语义的近义词quite掌握不够灵活，表达单一。     

Feature screening in ultrahigh-dimensional additive Cox model

The additive Cox model is flexible and powerful for modelling the dynamic changes of regression coefficients in the survival analysis. This paper is concerned with feature screening for the additive Cox model with ultrahigh-dimensional covariates. The proposed screening procedure can effectively identify active predictors. That is, with probability tending to one, the selected variable set includes the actual active predictors. In order to carry out the proposed procedure, we propose an effective algorithm and establish the ascent property of the proposed algorithm. We further prove that the proposed procedure possesses the sure screening property. Furthermore, we examine the finite sample performance of the proposed procedure via Monte Carlo simulations, and illustrate the proposed procedure by a real data example.     

Interval-valued data regression using partial linear model

Semi-parametric modelling of interval-valued data is of great practical importance, as exampled by applications in economic and financial data analysis. We propose a flexible semi-parametric modelling of interval-valued data by integrating the partial linear regression model based on the Center & Range method, and investigate its estimation procedure. Furthermore, we introduce a test statistic that allows one to decide between a parametric linear model and a semi-parametric model, and approximate its null asymptotic distribution based on wild Bootstrap method to obtain the critical values. Extensive simulation studies are carried out to evaluate the performance of the proposed methodology and the new test. Moreover, several empirical data sets are analysed to document its practical applications.     

Asymptotic hypothesis test to simultaneously compare the weighted kappa coefficients of multiple binary diagnostic tests in the presence of ignorable missing data

The weighted kappa coefficient of a binary diagnostic test is a measure of the beyond-chance agreement between the diagnostic test and the gold standard, and is a measure that allows us to assess and compare the performance of binary diagnostic tests. In the presence of partial disease verification, the comparison of the weighted kappa coefficients of two or more binary diagnostic tests cannot be carried out ignoring the individuals with an unknown disease status, since the estimators obtained would be affected by verification bias. In this article, we propose a global hypothesis test based on the chi-square distribution to simultaneously compare the weighted kappa coefficients when in the presence of partial disease verification the missing data mechanism is ignorable. Simulation experiments have been carried out to study the type I error and the power of the global hypothesis test. The results have been applied to the diagnosis of coronary disease.