Approximate Inference for the Factor Loading of a Simple Factor Analysis Model

We study a factor analysis model with two normally distributed observations and one factor. Two approximate conditional inference procedures for the factor loading are developed. The first proposal is a very simple procedure but it is not very accurate. The second proposal gives extremely accurate results even for very small sample size. Moreover, the calculations require only the signed log-likelihood ratio statistic and a measure of the standardized maximum likelihood departure. Simulations are used to study the accuracy of the proposed procedures.     

Local sensitivity approximations for selectivity bias

Observational data analysis is often based on tacit assumptions of ignorability or randomness. The paper develops a general approach to local sensitivity analysis for selectivity bias, which aims to study the sensitivity of inference to small departures from such assumptions. If M is a model assuming ignorability, we surround M by a small neighbourhood N defined in the sense of Kullback–Leibler divergence and then compare the inference for models in N with that for M . Interpretable bounds for such differences are developed. Applications to missing data and to observational comparisons are discussed. Local approximations to sensitivity analysis are model robust and can be applied to a wide range of statistical problems.     

A diagnostic for selecting the threshold in extreme value analysis

A new approach is suggested for choosing the threshold when fitting the Hill estimator of a tail exponent to extreme value data. Our method is based on an easily computed diagnostic, which in turn is founded directly on the Hill estimator itself, 'symmetrized' to remove the effect of the tail exponent but designed to emphasize biases in estimates of that exponent. The attractions of the method are its accuracy, its simplicity and the generality with which it applies. This generality implies that the technique has somewhat different goals from more conventional approaches, which are designed to accommodate the minor component of a postulated two-component Pareto mixture. Our approach does not rely on the second component being Pareto distributed. Nevertheless, in the conventional setting it performs competitively with recently proposed methods, and in more general cases it achieves optimal rates of convergence. A by-product of our development is a very simple and practicable exponential approximation to the distribution of the Hill estimator under departures from the Pareto distribution.     

Two sets of isotones for comparing tests of exponentiality

Isotones   are a deterministic graphical device introduced by Mudholkar et al. [1991. A graphical procedure for comparing goodness-of-fit tests. J. Roy. Statist. Soc. B 53, 221–232], in the context of comparing some tests of normality. An isotone of a test is a contour of p$p$ values of the test applied to “ideal samples”, called profiles, from a two-shape-parameter family representing the null and the alternative distributions of the parameter space. The isotone is an adaptation of Tukey's sensitivity curves, a generalization of Prescott's stylized sensitivity contours, and an alternative to the isodynes   of Stephens. The purpose of this paper is two fold. One is to show that the isotones can provide useful qualitative information regarding the behavior of the tests of distributional assumptions other than normality. The other is to show that the qualitative conclusions remain the same from one two-parameter family of alternatives to another. Towards this end we construct and interpret the isotones of some tests of the composite hypothesis of exponentiality, using the profiles of two Weibull extensions, the generalized Weibull and the exponentiated Weibull families, which allow IFR, DFR, as well as unimodal and bathtub failure rate alternatives. Thus, as a by-product of the study, it is seen that a test due to Csörg? et al. [1975. Application of characterizations in the area of goodness-of-fit. In: Patil, G.P., Kotz, S., Ord, J.K. (Eds.), Statistical Distributions in Scientific Work, vol. 2. Reidel, Boston, pp. 79–90], and Gnedenko's Q(r)$Q(r)$ test [1969. Mathematical Methods of Reliability Theory. Academic Press, New York], are appropriate for detecting monotone failure rate alternatives, whereas a bivariate F$F$ test due to Lin and Mudholkar [1980. A test of exponentiality based on the bivariate F$F$ distribution. Technometrics 22, 79–82] and their entropy test [1984. On two applications of characterization theorems to goodness-of-fit. Colloq. Math. Soc. Janos Bolyai 45, 395–414] can detect all alternatives, but are especially suitable for nonmonotone failure rate alternatives.     

广义经济学

回顾了火用经济学的历史及发展 ,通过对热力学系统与经济学系统的相似性比较 ,将广义火用的概念引入到经济学系统中来 ,并由此建立资本品质的概念 ,进而建立起以核算资本火用参量为基准的新型经济学理论。对广义火用经济学的若干状态参量的建立及定义作了初步探讨。     

小型光泵腔式NH3分子远红外激光器工作参数优化的实验研究

实验上采用金属网栅耦合的小型腔式NH3 分子远红外激光器 ,用TEA -CO2 激光器的 1 0R(8)和 9R(1 6)谱线作泵浦 ,获得了 2 81 μm和 90 .4μm的远红外激光 ,并对该激光器工作参数的优化进行了系统的实验研究     

基于MasterCAM的模具数控加工过程分析与应用

模具零件因其复杂的空间形面和形面特征而广泛采用数控加工方式。以常见的凹槽模具为例,基于MasterCAM对其数控加工过程进行了分析和参数设定。运用不同铣削方法完成了粗、精加工程序的编制与仿真,分析比较了典型的粗、精加工组合方式的加工质量和加工时间,确定了合理、高效的铣削方法。旨在探索一种优质、高效的数控加工方法,保汪加工精度和质量、缩短产品生产周期、降低加工成本。     

气候变化对农业的影响及应对措施

阐述气候变化的特点,分析农作物对温度、降水变化的敏感性,昆虫对温度变化的敏感性。探讨了农业生产对低温雨雪冰冻天气、对干旱及洪涝灾害的脆弱性。应对气候变化的农业技术选择包括选育抗逆性强的农作物新品种,增强农作物抵御自然灾害的能力;加强农业水利基础设施建设;大力发展节水农业种植技术;加强农业灾害性天气的预警与响应能力建设。在此基础上提出应对气候变化的农业适应性政策措施：调整耕作制度,提高复种指数;完善江河湖泊防洪工程和防洪减灾体系;加强土地合理利用;发展设施农业,提高农业抗御自然灾害的能力;制订减灾应急预案;积极推广农业保险。     

煤矿企业应急救援能力评估

对煤矿企业应急救援能力进行评估,可促进煤矿应急救援体系的建设。本文从组织管理、制度建设、保障系统、人力资源4个方面建立了煤矿企业应急救援能力的评估指标体系,并用模糊决策参数法确定指标属性值,且分为两个阶段,先由权威专家确定语言值,再由普通专家在相应的模糊集内评估,案例分析表明,该方法有效可行。     

Q235钢静载拉伸磁记忆检测试验

为了研究磁记忆信号和应力之间的关系,采用磁记忆方法检测单向静载拉伸后Q235钢板表面磁场强度法向分 量Hp(y),并设计了更方便检测的拉伸试样。结果表明Q235试件断裂前磁场法向分量检测曲线为斜直线,具有唯一的 极性翻转点。同时还发现Q235材料处在弹性阶段时磁参数m值变化较慢,在塑性变形阶段时磁参数m值变化较快。