造假行为的传播与遏制——基于进化博弈模拟的研究

借鉴进化博弈的思想,一个新的模型建立起来用以模拟造假行为的传播过程,以期找到其广泛传播的路径,并寻找遏制的方法。模型赋予了个体学习的能力,结果显示惩罚程度对造假行为的传播没有影响,但抽查概率却是决定性的。为了提高查处的效率,"连带检查"机制被加入到模型中,即对造假者周围邻居进行检查并施以同样的惩罚。这种机制能够在抽取概率为26%时达到消除造假者的目的,相比之下,没有"连带检查"时必须把抽取概率提高到80%才能达到消除造假者的目的。     

Computation of an efficient and robust estimator in a semiparametric mixture model

In this article, we propose an efficient and robust estimation for the semiparametric mixture model that is a mixture of unknown location-shifted symmetric distributions. Our estimation is derived by minimizing the profile Hellinger distance (MPHD) between the model and a nonparametric density estimate. We propose a simple and efficient algorithm to find the proposed MPHD estimation. Monte Carlo simulation study is conducted to examine the finite sample performance of the proposed procedure and to compare it with other existing methods. Based on our empirical studies, the newly proposed procedure works very competitively compared to the existing methods for normal component cases and much better for non-normal component cases. More importantly, the proposed procedure is robust when the data are contaminated with outlying observations. A real data application is also provided to illustrate the proposed estimation procedure.     

洛必答法则使用技巧及注意事项浅析

洛必答法则是求解极限的一个非常重要的方法,一般教材的编写,只是着重例题类型的分类专门讨论,在技巧的讨论上着墨较少,文章则从洛必答法则使用技巧以及注意事项方面针对一些实例做出浅析.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

浅谈洁净手术部在医院基建工程中的特殊需求

随着现代医学的发展,洁净手术部成为各手术学科建设与发展的重要前提与支柱,对原有手术室功能进行改造势在必行。为了实现医院洁净手术部向信息化、智能化、集约化发展,从洁净手术部的选址、功能等方面介绍了当前省内部分二级以上医疗单位洁净手术室建设的新进展,总结近年来在洁净手术室规划、建设过程中的经验,为现代医院基建工程管理提供借鉴,保障医院医疗、教学、科研工作的顺利开展。     

Convergence rates for uniform confidence intervals based on local polynomial regression estimators

We investigate the convergence rates of uniform bias-corrected confidence intervals for a smooth curve using local polynomial regression for both the interior and boundary region. We discuss the cases when the degree of the polynomial is odd and even. The uniform confidence intervals are based on the volume-of-tube formula modified for biased estimators. We empirically show that the proposed uniform confidence intervals attain, at least approximately, nominal coverage. Finally, we investigate the performance of the volume-of-tube based confidence intervals for independent non-Gaussian errors.     

Quality self-control and co-supervision mechanism of construction agent in public investment project in China

Public investment project (PIP) plays an important role in the China economy. In order to improve the project management performance of public projects, the government is searching for a scientific system to build a construction management supervision mode. This paper introduces the policy background and connotation of Agent Construction System (ACS). As a public investment construction management model, ACS, is gradually being incorporated into the legal framework, it is necessary to improve the construction agent supervision mechanism. This article analyzes the supervision mechanism of construction agent quality management under the principle of two-stage agent mode and establishes an agent quality self-control system and a government co-supervision system. These systems take the contract management as the core and the project quality objective as the guidance. These systems also consist of a two-dimensional framework of vertical self-control and horizontal supervision, which form a quality supervision mechanism. Based on Rough Set theory, the article proposes the idea of building an agent quality self-control and government co-supervision model, and illustrates it with a flow chart for building the model, which paves the way of quantitative research for the future.     

Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

Complete convergence and the strong laws of large numbers for pairwise NQD random variables

The authors study the strong convergence for sequences of pairwise negatively quadrant dependent (NQD) random variables under some wide conditions, and present some new theorems on the complete convergence and the strong laws of large numbers. The obtained results extend and improve some theorems in existing literature.