某高架桥分岔处局部应力分析

对某高架桥分岔处局部应力进行仿真分析。按照实际施工过程,考虑最不利计算荷载,根据平截面假定,分别对钢梁单独受力和钢-混凝土组合梁两种工况进行计算。结果表明分岔处整体受力良好,安全储备大。     

Cox模型和寿险退保研究中的比例危险性

利用生存分析研究寿险退保问题是一个很好的工具，因为可以将寿险保单的持续期（persistency duration）视为生存期长，而将保单的退保或失效看作一个“保单生命”的结束，这其中的保单退保或失效就成为生存研究的目标事件。而导致保单失效的因素会有很多，只有通过利用Cox比例危险模型拟合寿险退保数据以分析影响客户退保的原因，并在对Cox模型的比例危险假设进行检验时，发现部分影响因素并不遵守此前提条件，从而推理得到这些影响因素在不同的时间段对客户退保的影响方式不同。也就是说，其影响有短期效应和长期效应之分。     

Employment, family union and childbearing decisions in Great Britain

Summary.  The paper investigates the life-cycle relationship of work and family life in Britain based on the British Household Panel Survey. Using hazard regression techniques we estimate a five-equation model, which includes birth events, union formation, union dissolution, employment and non-employment events. We find that transitions in and out of employment for men are relatively independent of other transitions. In contrast, there are strong links between employment of females, having children and union formation. By undertaking a detailed microsimulations analysis, we show that different levels of labour force participation by females do not necessarily lead to large changes in fertility events. Changes in union formation and fertility events, in contrast, have larger effects on employment.     

我国经济转型时期企业员工人性的调查与分析

从管理学的角度来看,人性假设是指企业领导者和管理者对员工的工作态度、工作动机和工作需要等方面的基本认识和态度。本文以我国经济转型时期为背景,在实际调查的基础上对我国企业员工人性的主要特征进行了初步的分类和探析。     

公司分立中债权人保护法律制度比较研究

在公司分立中,分立公司的债权人利益很容易受损,如何保护债权人的利益,是公司分立制度中最重要的问题之一。应参酌其他国家和地区的相关立法例,完善我国的债权人保护制度。公司应当自作出分立决议之日起一定期限内实施债权人保护程序,债权人应无权直接阻却公司分立;分立公司的债务应由分立后的有关公司承担,明确有关公司承担或不承担连带责任的情形;明确分立公司的债务保证人承担或不承担相关责任的情形;应给予公司债持有人以特殊保护。     

Semiparametric Time-Varying Coefficients Regression Model for Longitudinal Data

Abstract.  In this paper, we consider a semiparametric time-varying coefficients regression model where the influences of some covariates vary non-parametrically with time while the effects of the remaining covariates follow certain parametric functions of time. The weighted least squares type estimators for the unknown parameters of the parametric coefficient functions as well as the estimators for the non-parametric coefficient functions are developed. We show that the kernel smoothing that avoids modelling of the sampling times is asymptotically more efficient than a single nearest neighbour smoothing that depends on the estimation of the sampling model. The asymptotic optimal bandwidth is also derived. A hypothesis testing procedure is proposed to test whether some covariate effects follow certain parametric forms. Simulation studies are conducted to compare the finite sample performances of the kernel neighbourhood smoothing and the single nearest neighbour smoothing and to check the empirical sizes and powers of the proposed testing procedures. An application to a data set from an AIDS clinical trial study is provided for illustration.     

Maximum Likelihood Estimation for Cox's Regression Model Under Case–Cohort Sampling

Abstract.  Case–cohort sampling aims at reducing the data sampling and costs of large cohort studies. It is therefore important to estimate the parameters of interest as efficiently as possible. We present a maximum likelihood estimator (MLE) for a case–cohort study based on the proportional hazards assumption. The estimator shows finite sample properties that improve on those by the Self & Prentice [Ann. Statist. 16 (1988)] estimator. The size of the gain by the MLE varies with the level of the disease incidence and the variability of the relative risk over the considered population. The gain tends to be small when the disease incidence is low. The MLE is found by a simple EM algorithm that is easy to implement. Standard errors are estimated by a profile likelihood approach based on EM-aided differentiation.     

A class of partially linear single‐index survival models

The authors define a class of “partially linear single‐index” survival models that are more flexible than the classical proportional hazards regression models in their treatment of covariates. The latter enter the proposed model either via a parametric linear form or a nonparametric single‐index form. It is then possible to model both linear and functional effects of covariates on the logarithm of the hazard function and if necessary, to reduce the dimensionality of multiple covariates via the single‐index component. The partially linear hazards model and the single‐index hazards model are special cases of the proposed model. The authors develop a likelihood‐based inference to estimate the model components via an iterative algorithm. They establish an asymptotic distribution theory for the proposed estimators, examine their finite‐sample behaviour through simulation, and use a set of real data to illustrate their approach.     

Benefit Analysis for Natural Hazards

The objective of this paper is to develop the ex ante perspective for benefit analysis with natural hazards. It defines an ex ante evaluation of the economic benefits that arise from policies designed to reduce either the risk of or the detrimental effects associated with a natural hazard. In the process the paper compares the ex ante and ex post perspectives and discusses the prospects for implementing the framework by measuring the valuation concepts that are developed.     

A Semi-parametric Bayesian Analysis of Survival Data Based on Lévy-driven Processes

In the presence of covariate information, the proportional hazards model is one of the most popular models. In this paper, in a Bayesian nonparametric framework, we use a Markov (Lévy-driven) process to model the baseline hazard rate. Previous Bayesian nonparametric models have been based on neutral to the right processes, which have a number of drawbacks, such as discreteness of the cumulative hazard function. We allow the covariates to be time dependent functions and develop a full posterior analysis via substitution sampling. A detailed illustration is presented.