Computing maximum likelihood estimates from type II doubly censored exponential data

It is well-known that, under Type II double censoring, the maximum likelihood (ML) estimators of the location and scale parameters, θ and δ, of a twoparameter exponential distribution are linear functions of the order statistics. In contrast, when θ is known, theML estimator of δ does not admit a closed form expression. It is shown, however, that theML estimator of the scale parameter exists and is unique. Moreover, it has good large-sample properties. In addition, sharp lower and upper bounds for this estimator are provided, which can serve as starting points for iterative interpolation methods such as regula falsi. Explicit expressions for the expected Fisher information and Cramér-Rao lower bound are also derived. In the Bayesian context, assuming an inverted gamma prior on δ, the uniqueness, boundedness and asymptotics of the highest posterior density estimator of δ can be deduced in a similar way. Finally, an illustrative example is included.     

政府部门与企业人员培训管理的差异比较与评价研究

培训是人力资源开发的主要手段。政府部门和企业作为两种不同的组织形态,在组织目标、组织结构、组织文化、组织环境上存在明显差异,这些差异的存在使得两类组织在内部人员培训侧重点、培训目标、培训管理体制和培训法律依据等方面存在本质上的不同。在培训管理现状上,政府部门与企业在培训制度的完备程度、培训管理的规范与否、培训渠道是否多样、培训基础建设和培训实效的重视程度上都存在差异,且各有优势。为促进两类组织在培训方面的共同提高,政府部门与企业应相互学习。企业应学习政府部门重视思想素质的培训、培训管理体系的建立和培训基础工作的夯实,政府部门应学习企业重视培训实效的加强和培训途径的开拓。     

国画与阴阳辩证法

本文认为国画具体地体现着阴阳辩证法 ,它集中地表现为“象”与“意”的关系 ,又具体实现在辩证的构图和技法中     

关于社会对技术的必要约束——评技术价值中立论与价值自主论

技术的价值在于它可以物化为人造物 ,用来取代天然自然物和人自身。这种取代的成功导致了人类的“技术化生存”。现代技术有可能导致人的全面异化 ,所以对技术的研究与应用应加以必要的、合理的约束。技术价值中立论认为技术不涉及善恶问题 ,会导致对技术的无任何约束。这种观点是错误的。技术有禁区 ,如果技术研究同人类的根本利益相悖 ,就应当禁止。应提倡技术人道主义原则 ,这就需要摈弃认为技术自我决定、不受任何约束的技术至上论或技术自主论     

国际人权公约与我国人权立法的比较

本文通过国际人权公约和我国人权立法的比较,可以看到我国人权立法与世界共同标准不断接近的轨迹.尽管权利的确立和保障,要受一国经济、社会和文化发展水平的制约,采取的步骤应与一国的国情和承受能力相适应.但毫无疑问,继续缩小两者的差异,解决相互间的冲突,是我国人权立法完善和前进的方向.     

大学生创造性人格调查分析

21世纪人才素质的核心是创造性素质。创造性素质 ,主要指一个人的创新意识、创造性思维能力以及创造性人格品质。本研究利用卡氏十六种人格因素测验量表 (16 PF)对北京邮电大学本科生的创造性人格进行测试 ,分析表明影响人的创造力的因素是复杂的。创造性是可以通过教育进行培养的 ,关键是要通过教育改革创造条件 ,允许和鼓励人的个性的发展     

Adapting by calibration the sample size of a phase III trial on the basis of phase II data

The problem of estimating the sample size for a phase III trial on the basis of existing phase II data is considered, where data from phase II cannot be combined with those of the new phase III trial. Focus is on the test for comparing the means of two independent samples. A launching criterion is adopted in order to evaluate the relevance of phase II results: phase III is run if the effect size estimate is higher than a threshold of clinical importance. The variability in sample size estimation is taken into consideration. Then, the frequentist conservative strategies with a fixed amount of conservativeness and Bayesian strategies are compared. A new conservative strategy is introduced and is based on the calibration of the optimal amount of conservativeness – calibrated optimal strategy (COS). To evaluate the results we compute the Overall Power (OP) of the different strategies, as well as the mean and the MSE of sample size estimators. Bayesian strategies have poor characteristics since they show a very high mean and/or MSE of sample size estimators. COS clearly performs better than the other conservative strategies. Indeed, the OP of COS is, on average, the closest to the desired level; it is also the highest. COS sample size is also the closest to the ideal phase III sample size M_I, showing averages and MSEs lower than those of the other strategies. Costs and experimental times are therefore considerably reduced and standardized. However, if the ideal sample size M_I is to be estimated the phase II sample size n should be around the ideal phase III sample size, i.e. n?2M_I/3. Copyright © 2010 John Wiley & Sons, Ltd.     

THE DUALITY DIAGRAM IN DATA ANALYSIS: EXAMPLES OF MODERN APPLICATIONS

Today's data-heavy research environment requires the integration of different sources of information into structured datasets that can not be analyzed as simple matrices. We introduce an old technique, known in the European data analyses circles as the Duality Diagram Approach, put to new uses through the use of a variety of metrics and ways of combining different diagrams together. This issue of the Annals of Applied Statistics contains contemporary examples of how this approach provides solutions to hard problems in data integration. We present here the genesis of the technique and how it can be seen as a precursor of the modern kernel based approaches.     

Assessing the pattern of covariance matrices via an augmentation multiple testing procedure

This paper extends the scedasticity comparison among several groups of observations, usually complying with the homoscedastic and the heteroscedastic cases, in order to deal with data sets laying in an intermediate situation. As is well known, homoscedasticity corresponds to equality in orientation, shape and size of the group scatters. Here our attention is focused on two weaker requirements: scatters with the same orientation, but with different shape and size, or scatters with the same shape and size but different orientation. We introduce a multiple testing procedure that takes into account each of the above conditions. This approach discloses a richer information on the data underlying structure than the classical method only based on homo/heteroscedasticity. At the same time, it allows a more parsimonious parametrization, whenever the patterned model is appropriate to describe the real data. The new inferential methodology is then applied to some well-known data sets, chosen in the multivariate literature, to show the real gain in using this more informative approach. Finally, a wide simulation study illustrates and compares the performance of the proposal using data sets with gradual departure from homoscedasticity.     

The Determinants of Blue CollarWage Rates: An Analysis of a DataSet Incorporating Observed Job Characteristics

There is wide agreement that one of the major problems in the estimation of wage equations, and in testing theories of wages, is the quality of the data available. In particular, the data used in almost all studies involve indirect or unsatisfactory measures of a variety of relevant factors, including working conditions. In this paper we exploit an unusual data set that includes measures of characteristics of jobs generated by observation (rather than self report, or through inference from the Dictionary of Occupational Titles). With these data we estimate a wage equation in which compensating differentials play a significant role in wage determination and, once working conditions and other characteristics are effectively controlled, all but one measure of previous labour market experience had no effect on the wage rate.