基于核心制造规范的外包决策模型及实证研究

本文将制造规范概念引入外包决策,从考虑企业长期绩效和长期竞争力的角度提出了一个以制造规范核心度和流失度为控制变量的二维外包决策模型。决策模型将外包环境分为九种类型,涵盖了从内部制造、各种形式的外包,到简单采购等所有"买或做"的决策,尤其是对介于自制与简单采购之间灰色地带的外包,给出了考虑提供制造规范主体和供应商类型的不同类型合作和联盟治理结构策略。对四个不同类型的企业典型产品近1000个零件的外包决策进行了统计分析,实证了模型的有效性。模型对现实世界观察到的制造企业由于没有按照其中规律行事而导致失败的原因做出了合理而明确解释。     

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well-known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given.     

附条件逮捕之理论初探

附条件逮捕发端于司法实践,对协调办案需要和人权保障意义重大。但各地运行状况并不统一,学界也存在着一定的理论争议。对此可以从文本认同、理论认同和感情认同三个角度加以探讨,既指出理论质疑,也阐明其存在的合理性和改善的必要性。     

The information matrix test in the linear regression with ARMA errors

Summary The paper shows that the informaton matrix test presented by White (1982) decomposes into the sum of quadratic forms in the case of a linear model with ARMA errors. By extending previous results, which analysed the information matrix test in the presence of serial correlation, the test allows detection of additional sources of misspecification.     

激光散斑相位差的条件统计分布与表面粗糙度的关系

在粗糙表面高度起伏服从高斯统计和表面服从圆型相关的情况下，分析了由弱散射体产生的远场高斯激光散斑相位差的条件统计分布与表面粗糙度的关系．     

实践性·具体性·系统性--全面贯彻"三个代表"重要思想的方法论原则探论

要使"三个代表"重要思想真正成为全党在实际工作中长期坚持的指导思想,就必须正确解决实现"三个代表"重要思想的科学方法论问题,切实按照马克思主义的实践性、具体性、系统性原则的要求,在贯彻"三个代表"重要思想过程中,始终做到"务实"与"务虚"、"共性"与"个性"、"部分"与"整体"的有机统一.     

Perfect simulation for correlated Poisson random variables conditioned to be positive

In this paper we present a perfect simulation method for obtaining perfect samples from collections of correlated Poisson random variables conditioned to be positive. We show how to use this method to produce a perfect sample from a Boolean model conditioned to cover a set of points: in W.S. Kendall and E. Thönnes (Pattern Recognition 32(9): 1569–1586, 1999), this special case was treated in a more complicated way. The method is applied to several simple examples where exact calculations can be made, so as to check correctness of the program using ²-tests, and some small-scale experiments are carried out to explore the behaviour of the conditioned Boolean model.     

Empirical Uncertain Bayes Methods in Area‐level Models

Random effects model can account for the lack of fitting a regression model and increase precision of estimating area‐level means. However, in case that the synthetic mean provides accurate estimates, the prior distribution may inflate an estimation error. Thus, it is desirable to consider the uncertain prior distribution, which is expressed as the mixture of a one‐point distribution and a proper prior distribution. In this paper, we develop an empirical Bayes approach for estimating area‐level means, using the uncertain prior distribution in the context of a natural exponential family, which we call the empirical uncertain Bayes (EUB) method. The regression model considered in this paper includes the Poisson‐gamma and the binomial‐beta, and the normal‐normal (Fay–Herriot) model, which are typically used in small area estimation. We obtain the estimators of hyperparameters based on the marginal likelihood by using a well‐known expectation‐maximization algorithm and propose the EUB estimators of area means. For risk evaluation of the EUB estimator, we derive a second‐order unbiased estimator of a conditional mean squared error by using some techniques of numerical calculation. Through simulation studies and real data applications, we evaluate a performance of the EUB estimator and compare it with the usual empirical Bayes estimator.     

供应突发事件下基于CVaR的供应链订货决策及协调

供应突发事件下,引入条件风险值(conditional value at risk-CVa R)刻画了零售商的运营目标,构建了收益共享契约下的供应链订货模型,着重研究了CVa R下的供应链协调及零售商最优订货量对供应商可靠性及对其自身的风险规避系数的敏感性。研究表明:收益共享契约具有一定的鲁棒性,能协调突发事件风险下的供应链;风险规避型零售商的最优订货量总是不小于风险中性情况,且风险规避程度越高,订货量越大;最优订货量对供应商可靠性均值的敏感性不依赖于零售商的风险规避程度,且均值越小,最优订货量越大,这与风险中性情况是类似的;最优订货量对供应商可靠性标准差的敏感性则依赖于零售商的风险规避程度,当零售商的风险规避程度较高时,供应可靠性标准差越大,最优订货量越大,这与风险中性情况是相反的。     

超高频数据的日内效应调整方法研究

日内效应在金融高频数据研究中已被广泛证实,是一种日内周期性运动的动态效应,它影响了以微观金融指标为参数的计量模型的准确估计。基于金融超高频持续期数据,本文首先论述了日内效应调整的重要性,然后引入自适应映射(SOM)的方法对日内效应进行调整。SOM是一种基于神经网络学习的特征提取方法,能够动态识别高维数据中的结构特征,克服了静态调整方法的不足。最后通过建立基于自回归条件持续期模型(ACD)的蒙特卡罗模拟实验,比较了三种日内效应调整方法的效果。模拟结果表明SOM方法在日内效应调整中更为有效和稳定,特别适合大数据条件下的周期性结构分析。