Survival and lifetime data analysis with a flexible class of distributions

We introduce a general class of continuous univariate distributions with positive support obtained by transforming the class of two-piece distributions. We show that this class of distributions is very flexible, easy to implement, and contains members that can capture different tail behaviours and shapes, producing also a variety of hazard functions. The proposed distributions represent a flexible alternative to the classical choices such as the log-normal, Gamma, and Weibull distributions. We investigate empirically the inferential properties of the proposed models through an extensive simulation study. We present some applications using real data in the contexts of time-to-event and accelerated failure time models. In the second kind of applications, we explore the use of these models in the estimation of the distribution of the individual remaining life.     

积分变换求梁的变形

本文从求解梁挠度的二阶差分方程出发，通过Z变换，最后推导出计算挠度和转角的简单公式，使计算过程简化。对于变截面梁和复杂受载下，此法尤为简便。同时，这也是处理离散参数的数学方法—Z变换在力学中应用的初步尝试。     

Bayesian penalized B-spline estimation approach for epidemic models

Ordinary differential equations (ODEs) are normally used to model dynamic processes in applied sciences such as biology, engineering, physics, and many other areas. In these models, the parameters are usually unknown, and thus they are often specified artificially or empirically. Alternatively, a feasible method is to estimate the parameters based on observed data. In this study, we propose a Bayesian penalized B-spline approach to estimate the parameters and initial values for ODEs used in epidemiology. We evaluated the efficiency of the proposed method based on simulations using the Markov chain Monte Carlo algorithm for the Kermack–McKendrick model. The proposed approach is also illustrated based on a real application to the transmission dynamics of hepatitis C virus in mainland China.     

现代社会转型与法治政府的变革路径

伴随着中国改革开放的进程,转型成为社会变迁的主题和基本特征。与此相应的却是,改革日益呈现出一种“锁定”的状态。在社会转型时期出现的诸多根本性问题,并不能用过渡性的办法来解决。在国家和法律的现代化进程中,特别是构建法治政府的进程中,政府不能再像过去那样,一味运用相机决策和政策调整来处理社会利益矛盾,不能再对不同群体在基本权利上区别对待。同样,在工农、城乡、区域乃至人与自然生态之间,要实现统筹协调发展的目标,更需要加强普遍性的努力,这种普遍性努力以法治和体现法治精神的整体性政策为特征。     

Sensitivity Analysis Using Risk Measures

In a quantitative model with uncertain inputs, the uncertainty of the output can be summarized by a risk measure. We propose a sensitivity analysis method based on derivatives of the output risk measure, in the direction of model inputs. This produces a global sensitivity measure, explicitly linking sensitivity and uncertainty analyses. We focus on the case of distortion risk measures, defined as weighted averages of output percentiles, and prove a representation of the sensitivity measure that can be evaluated on a Monte Carlo sample, as a weighted average of gradients over the input space. When the analytical model is unknown or hard to work with, nonparametric techniques are used for gradient estimation. This process is demonstrated through the example of a nonlinear insurance loss model. Furthermore, the proposed framework is extended in order to measure sensitivity to constant model parameters, uncertain statistical parameters, and random factors driving dependence between model inputs.     

Asymptotic theory for maximum likelihood estimates in reduced-rank multivariate generalized linear models

Reduced-rank regression is a dimensionality reduction method with many applications. The asymptotic theory for reduced rank estimators of parameter matrices in multivariate linear models has been studied extensively. In contrast, few theoretical results are available for reduced-rank multivariate generalized linear models. We develop M-estimation theory for concave criterion functions that are maximized over parameter spaces that are neither convex nor closed. These results are used to derive the consistency and asymptotic distribution of maximum likelihood estimators in reduced-rank multivariate generalized linear models, when the response and predictor vectors have a joint distribution. We illustrate our results in a real data classification problem with binary covariates.     

基于盾构掘进参数的LVQ神经网络地层识别

以苏州4号线2标及2号线东延伸线5标地铁工程为背景，分析了盾构机的掘进参数：千斤顶推力、推进速度、刀盘扭矩、螺旋机转速和同步注浆量在不同地层条件下的变化规律。提出了基于盾构机掘进参数的学习向量量化（Learning Vector Quantization，LVQ）神经网络地层识别方法。建立了以盾构机五个掘进参数作为输入，地层特性编码为输出的数学模型，通过每种地层100组训练样本对模型进行训练，通过57步训练，训练样本误差控制在0.1以内，并用每种地层50组检验样本进行检验，地层总体识别率达到82.7%。     

关注利益相关者与实现民营外贸企业成功转型的关系研究

入世后,我国民营外贸企业得到了迅猛的发展,目前已基本完成了"量"的积累,进入了全面转型和提升"质"的阶段。民营外贸企业要突破当前的发展困境,必须关注企业的内外部利益相关者,只有得到他们的充分理解与大力支持,才能成功实现企业的转型。     

A monte carlo evaluation of response surface analysis based on paired-comparison data

The use of the logit transformation on paired-comparison data in the weighted least squares analysis of response surfaces for aesthetic qualities of products is discussed. Monte Carlo simulations are employed to investigate the small sample properties of the estimators and test statistics. A secondary objective of the Monte Carlo simulations is the comparison of two transformation procedures. The simulations are of standard-item paired-compar-ison experiments in which ties are not allowed.     

Sequential estimation problems for negative exponential populations

The literature on sequential estimation problems for negative exponential populations has been reviewed here, We attempt to bring in all the published and unpublished materials known to us in a fairly coherent fashion. Both the concepts and theoretical findings are discussed.