农业保险的保障水平与财政补贴政策优化：一个文献综述 *

近年来，我国农业保险快速发展，在保费收入、保障范围和参保农户数量等指标上都取得了举世瞩目的成绩。与此同时，保障水平不高、农业保险“不解渴、不顶用”也一直是各方反映的焦点之一。本文结合了福利经济学和保险经济学中的相关理论，遵循“提高农业保险保障水平必须优化其财政补贴政策”的逻辑主线，对实施财政补贴政策是提升农业保险保障水平的前提条件、有效途径、有力举措和重要渠道进行了梳理和评析。最后，针对现有研究的不足，结合当前的时代背景，对该领域日后的研究重点进行了预测，并进一步探讨了其优化路径。     

中国收入分配的公平与效率关系测度及评价

首先对公平与效率做出了精确定义,确定其指标,然后测度由于收入分配总量和结构引致的公平与效率的变化量,在此基础上构建了一个公平效率指数,用来反映中国二者关系的变化及其协调程度,最后采用目标优化的方法对收入分配总量和结构进行了优化,根据优化结果提出了改善收入分配关系的建议。     

Estimation of Mode Using Two-phase Sampling

In this article, we consider the problem of estimation of mode using two-phase sampling. Ratio- and difference-type estimators in two-phase sampling are proposed. The asymptotic properties of the proposed estimators are studied analytically as well as empirically for different situations for the given cost of surveys. The use of two-phase sampling has been found to be cost saving design while estimating mode by making a proper use of auxiliary information.     

中国金融对经济增长贡献的效率研究——金融发展的阶段划分及评价

通过聚类分析将改革开放以来的中国金融-经济系统分为传统金融时期、金融转型初期、金融转型中期三个阶段,然后选取资本存量、劳动力、金融机构人民币资金来源、M2、贷款余额作为投入变量,GDP作为产出变量,采用非径向超效率分析模型测度中国金融效率。研究表明:中国的金融-经济系统存在结构变化,金融的绝对效率较低,但相对效率水平较高,中国已经顺利完成了金融体系的转型。     

Another look at the robustness of colton's model for comparing two medical treatments

The robustness of an extended version of Colton's decision theoretic model is considered. The extended version includes the losses due to the patients who are not entered in the experiment, but require treatment while the experiment is in progress. Among the topics considered are the effects of risk of using a sample size considerably less than the optimum, use of an incorrect patient horizon, application of a modified loss function, and use of a two point prior distribution. It is shown that the investigated model is robust with respect to all these changes with the exception of the use of the modified prior density.     

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。     

Double shrinkage estimators for large sparse covariance matrices

Covariance matrices play an important role in many multivariate techniques and hence a good covariance estimation is crucial in this kind of analysis. In many applications a sparse covariance matrix is expected due to the nature of the data or for simple interpretation. Hard thresholding, soft thresholding, and generalized thresholding were therefore developed to this end. However, these estimators do not always yield well-conditioned covariance estimates. To have sparse and well-conditioned estimates, we propose doubly shrinkage estimators: shrinking small covariances towards zero and then shrinking covariance matrix towards a diagonal matrix. Additionally, a richness index is defined to evaluate how rich a covariance matrix is. According to our simulations, the richness index serves as a good indicator to choose relevant covariance estimator.     

Adaptive designs for single‐arm phase II trials in oncology

Clinical phase II trials in oncology are conducted to determine whether the activity of a new anticancer treatment is promising enough to merit further investigation. Two‐stage designs are commonly used for this situation to allow for early termination. Designs proposed in the literature so far have the common drawback that the sample sizes for the two stages have to be specified in the protocol and have to be adhered to strictly during the course of the trial. As a consequence, designs that allow a higher extent of flexibility are desirable. In this article, we propose a new adaptive method that allows an arbitrary modification of the sample size of the second stage using the results of the interim analysis or external information while controlling the type I error rate. If the sample size is not changed during the trial, the proposed design shows very similar characteristics to the optimal two‐stage design proposed by Chang et al. (Biometrics 1987; 43:865–874). However, the new design allows the use of mid‐course information for the planning of the second stage, thus meeting practical requirements when performing clinical phase II trials in oncology. Copyright © 2012 John Wiley & Sons, Ltd.     

在公正与效率之间:证人出庭作证制度的困境和出路

证人出庭作证问题,涉及证明标准与法律假设、法律规则与法律标准、诉讼效率与诉讼成本、自利偏见与社会效应等诸多方面。证人不出庭作证的规范依据仍然存在、证人出庭作证的权利和义务不对等、配套措施不完善等原因,导致证人不愿意出庭。美国辩诉交易制度在很大程度上减少了开庭刑事案件的数量,其关于书面陈述的规定也减少了证人出庭作证的需求,在一定程度上实现了被告人人权保护和公共利益的平衡,值得借鉴。完善证人出庭作证制度,应以案件"客观需要"为标准,以追求事实真相为出发点,以人权保护和人性回归为落脚点,遵循限制性处罚原则和禁止利益冲突原则,提高相关规定的可操作性。因此,不宜盲目追求证人高出庭作证率。     

Testing variance components in balanced linear growth curve models

It is well known that the testing of zero variance components is a non-standard problem since the null hypothesis is on the boundary of the parameter space. The usual asymptotic chi-square distribution of the likelihood ratio and score statistics under the null does not necessarily hold because of this null hypothesis. To circumvent this difficulty in balanced linear growth curve models, we introduce an appropriate test statistic and suggest a permutation procedure to approximate its finite-sample distribution. The proposed test alleviates the necessity of any distributional assumptions for the random effects and errors and can easily be applied for testing multiple variance components. Our simulation studies show that the proposed test has Type I error rate close to the nominal level. The power of the proposed test is also compared with the likelihood ratio test in the simulations. An application on data from an orthodontic study is presented and discussed.