基于数量柔性契约的双源应急物资采购定价模型

针对灾害事件发生的不确定性以及灾害发生后应急物资需求量的爆发式增长，本文设计了一个政府主导的基于数量柔性契约的双源应急物资采购模型。在存在一个现货市场的情况下，政府除了常规采购外，还会与供应方签订一份数量柔性契约，用以建立政企联合储备应急物资的合作关系。通过数理推导，本文发现灾害事件发生概率，政府自身储备量，现货市场采购价格会对双方决策产生重要影响，并给出三个影响因素在满足不同条件时政企双方的最优决策，同时进一步分析了这三个因素对政府采购成本与供应方利润的影响。最后，通过数值模拟的方式对所得结论进行了验证。本文的研究为政府与企业构建联合储备应急物资的合作关系提供了指导与依据。     

存在议价能力和副产品协同生产的制造商最优产量决策

考虑由环保型制造商和处理厂构成的两级供应链结构，其中上游制造商进行主产品的生产，而下游处理厂通过对废料加工进行副产品的生产。基于供应链成员之间存在不同议价能力的情形，构建了上游制造商将产生的废料给下游进行处理的协同生产模式，给出了主产品的均衡产量决策和废料的最优交易价格以及制造商关于废料的最优处理策略。研究结果表明，制造商的废料处理策略取决于消费者对副产品产量的敏感程度。当消费者对副产品产量较敏感（不敏感）时，制造商会选择自己处理废料（给处理厂进行加工）。此外，随着制造商议价能力的上升，制造商的均衡利润上升，而处理厂的均衡利润下降。最后发现本文的基本结论在随机产出环境下依然稳健。     

Interval estimation for conformance proportions of multiple quality characteristics

A conformance proportion is an important and useful index to assess industrial quality improvement. Statistical confidence limits for a conformance proportion are usually required not only to perform statistical significance tests, but also to provide useful information for determining practical significance. In this article, we propose approaches for constructing statistical confidence limits for a conformance proportion of multiple quality characteristics. Under the assumption that the variables of interest are distributed with a multivariate normal distribution, we develop an approach based on the concept of a fiducial generalized pivotal quantity (FGPQ). Without any distribution assumption on the variables, we apply some confidence interval construction methods for the conformance proportion by treating it as the probability of a success in a binomial distribution. The performance of the proposed methods is evaluated through detailed simulation studies. The results reveal that the simulated coverage probability (cp) for the FGPQ-based method is generally larger than the claimed value. On the other hand, one of the binomial distribution-based methods, that is, the standard method suggested in classical textbooks, appears to have smaller simulated cps than the nominal level. Two alternatives to the standard method are found to maintain their simulated cps sufficiently close to the claimed level, and hence their performances are judged to be satisfactory. In addition, three examples are given to illustrate the application of the proposed methods.     

施肥量与垄作方式对牛蒡子出苗率及苗期生长的影响

从施肥量（高肥、中肥、低肥）、垄作方式（上垄、下垄、下垄覆膜）两因素对牛蒡子的出苗及苗期生长情况做了一些系统观察和分析．结果表明：低肥，上垄有利于出苗，高肥有利于苗期的生长．此研究可为牛蒡子的进一步开发利用及科研提供科学依据．     

信息不对称下价格随机的应急数量折扣契约研究

以市场需求和市场价格随机波动的二级供应链为研究对象，寻找其在信息不对称条件下绩效优化的路径。通过显示原理分别构建生产成本和销售成本信息不对称时应急供应链的数量折扣契约模型，得到最优订货量与最佳批发价策略。通过具体的算例加以验证，分析了信息不对称程度对供应链上成员及整个供应链绩效的影响。研究结果表明：当突发事件造成市场价格随机波动和市场需求变化时，供应链上的跟随者能从隐瞒私人信息中获利。但当市场需求增大时，整个供应链绩效受损，反之则反是。这与以往研究在市场需求随机、市场价格固定和信息不对称条件下的结论迥异。     

考虑订货协调成本与数量折扣的改良品供应链水平协调

在单个供应商与多个销售商构成的二级改良品供应链中，销售商们采用联合补货方式不仅可以分摊订货成本，而且由于订货批量的增加从而更易获得供应商提供的数量折扣合同。建立多个销售商在独立补货与联合补货中的利润水平函数，推导联合补货优于独立补货的充要条件。将销售商之间的联合补货行为转化成多人合作博弈问题，证明博弈具有的基本性质，设计基于博弈核心的利润分配方法。通过数值算例和敏感性分析验证了文中所构建模型的正确性。     

Simultaneous confidence intervals for one-way layout based on generalized pivotal quantities

In this paper, we consider simultaneous confidence intervals for all-pairwise comparisons of treatment means in a one-way layout under heteroscedasticity. Two kinds of simultaneous intervals are provided based on the fiducial generalized pivotal quantities of the interest parameters. We prove that they both have asymptotically correct coverage. Simulation results and an example are also reported. It is concluded from calculational evidence that the second kind of simultaneous confidence intervals, which we provide, performs better than existing methods.     

A new confidence interval in errors-in-variables model with known error variance

This paper considers constructing a new confidence interval for the slope parameter in the structural errors-in-variables model with known error variance associated with the regressors. Existing confidence intervals are so severely affected by Gleser–Hwang effect that they are subject to have poor empirical coverage probabilities and unsatisfactory lengths. Moreover, these problems get worse with decreasing reliability ratio which also result in more frequent absence of some existing intervals. To ease these issues, this paper presents a fiducial generalized confidence interval which maintains the correct asymptotic coverage. Simulation results show that this fiducial interval is slightly conservative while often having average length comparable or shorter than the other methods. Finally, we illustrate these confidence intervals with two real data examples, and in the second example some existing intervals do not exist.     

Generalized simultaneous confidence regions for regression coefficients and their ratios

This study constructs a simultaneous confidence region for two combinations of coefficients of linear models and their ratios based on the concept of generalized pivotal quantities. Many biological studies, such as those on genetics, assessment of drug effectiveness, and health economics, are interested in a comparison of several dose groups with a placebo group and the group ratios. The Bonferroni correction and the plug-in method based on the multivariate-t distribution have been proposed for the simultaneous region estimation. However, the two methods are asymptotic procedures, and their performance in finite sample sizes has not been thoroughly investigated. Based on the concept of generalized pivotal quantity, we propose a Bonferroni correction procedure and a generalized variable (GV) procedure to construct the simultaneous confidence regions. To address a genetic concern of the dominance ratio, we conduct a simulation study to empirically investigate the probability coverage and expected length of the methods for various combinations of sample sizes and values of the dominance ratio. The simulation results demonstrate that the simultaneous confidence region based on the GV procedure provides sufficient coverage probability and reasonable expected length. Thus, it can be recommended in practice. Numerical examples using published data sets illustrate the proposed methods.     

The effect of number of siblings on adult mortality: Evidence from Swedish registers for cohorts born between 1938 and 1972

Demographic research has paid much attention to the impact of childhood conditions on adult mortality. We focus on one of the key aspects of early life conditions, sibling group size, and examine the causal effect of growing up in a large family on mortality. While previous studies have focused on low- or middle-income countries, we examine whether growing up in a large family is a disadvantage in Sweden, a context where most parents have adequate resources, which are complemented by a generous welfare state. We used Swedish register data and frailty models, examining all-cause and cause-specific mortality between the ages of 40 and 74 for the 1938–72 cohorts, and also a quasi-experimental approach that exploited multiple births as a source of exogenous variation in the number of siblings. Overall our results do not indicate that growing up in a large family has a detrimental effect on longevity in Sweden.