The General Segmented Distribution

We develop a distribution supported on a bounded interval with a probability density function that is constructed from any finite number of linear segments. With an increasing number of segments, the distribution can approach any continuous density function of arbitrary form. The flexibility of the distribution makes it a useful tool for various modeling purposes. We further demonstrate that it is capable of fitting data with considerable precision—outperforming distributions recommended by previous studies. We suggest that this distribution is particularly effective in fitting data with sufficient observations that are skewed and multimodal.     

A general class of hierarchical ordinal regression models with applications to correlated roc analysis

The authors discuss a general class of hierarchical ordinal regression models that includes both location and scale parameters, allows link functions to be selected adaptively as finite mixtures of normal cumulative distribution functions, and incorporates flexible correlation structures for the latent scale variables. Exploiting the well‐known correspondence between ordinal regression models and parametric ROC (Receiver Operating Characteristic) curves makes it possible to use a hierarchical ROC (HROC) analysis to study multilevel clustered data in diagnostic imaging studies. The authors present a Bayesian approach to model fitting using Markov chain Monte Carlo methods and discuss HROC applications to the analysis of data from two diagnostic radiology studies involving multiple interpreters.     

A hierarchy of lorenz curves based on the generalized tukey's lambda distribution

A hierarchy of Lorenz curves based on the generalized Tukey's Lambda distribution is proposed. Representations of the corresponding distribution and density function are also provided, together with popular inequality measures. Estimation methods are suggested. Finally, a comparison with other parametric families of Lorenz curves is established.     

Improved attribute acceptance sampling plans based on maxima nomination sampling

This paper demonstrates the use of maxima nomination sampling (MNS) technique in design and evaluation of single AQL, LTPD, and EQL acceptance sampling plans for attributes. We exploit the effect of sample size and acceptance number on the performance of our proposed MNS plans using operating characteristic (OC) curve. Among other results, we show that MNS acceptance sampling plans with smaller sample size and bigger acceptance number perform better than commonly used acceptance sampling plans for attributes based on simple random sampling (SRS) technique. Indeed, MNS acceptance sampling plans result in OC curves which, compared to their SRS counterparts, are much closer to the ideal OC curve. A computer program is designed which can be used to specify the optimum MNS acceptance sampling plan and to show, visually, how the shape of the OC curve changes when parameters of the acceptance sampling plan vary. Theoretical results and numerical evaluations are given.     

Parental Work Schedules and Children's Cognitive Trajectories

Previous work has shown an association between mothers' nonstandard work schedules and children's well-being. We built on this research by examining the relationship between parental shift work and children's reading and math trajectories from age 5/6 to 13/14. Using data (N=7,105) from the National Longitudinal Survey of Youth and growth curve modeling, we found that children's math and reading trajectories were related to parents' type of nonstandard shifts (i.e., evening, night, or variable). We found that having a mother who worked more years at a night shift was associated with lower reading scores, having a mother work more years at evening or night shifts was associated with reduced math trajectories, and having a father work more years at an evening shift was associated with reduced math scores. Mediation tests suggest that eating meals together, parental knowledge about children's whereabouts, and certain after-school activities might help explain these results.     

论劳动力胀供给膨对宏观经济运行的不良影响

劳动力供给膨胀问题是一个严重的社会问题,劳动力供给膨胀对宏观经济的运行产生许多不良影响,集中体现在市场经济效率、社会财富分配、社会稳定三个方面。研究劳动力供给膨胀对一个国家构建和谐社会具有重要的理论意义和现实意义。     

Computing Optimal Beams in Two and Three Dimensions

The problem of computing an optimal beam among weighted regions (called the optimal beam problem) arises in several applied areas such as radiation therapy, stereotactic brain surgery, medical surgery, geological exploration, manufacturing, and environmental engineering. In this paper, we present computational geometry techniques that enable us to develop efficient algorithms for solving various optimal beam problems among weighted regions in two and three dimensional spaces. In particular, we consider two types of problems: the covering problems (seeking an optimal beam to contain a specified target region), and the piercing problems (seeking an optimal beam of a fixed shape to pierce the target region). We investigate several versions of these problems, with a variety of beam shapes and target region shapes in 2-D and 3-D. Our algorithms are based on interesting combinations of computational geometry techniques and optimization methods, and transform the optimal beam problems to solving a collection of instances of certain special non-linear optimization problems. Our approach makes use of interesting geometric observations, such as utilizing some new features of Minkowski sums.     

对称性在定积分中的应用

对称性在定积分中的应用孙军安，郑德印利用函数图形的对称性可简化定积分的计算。在特殊情况下，甚至可以求出原函数不是初等函数的定积分。因此掌握用对称性计算定积分的方法是必要的有益的。本文首先给出一个引理，由此得出一系列有趣的结果，并通过实例说明这些结果的...     

中西合璧的“圣女”——《典型的美国佬》中特蕾萨的性格分析

美籍华裔女作家任璧莲的代表作《典型的美国佬》中的特蕾萨,既保留了中国人的勤奋、善良和强烈的家庭责任感,又吸收了西方人坚强独立、勇于追求的开拓精神。东西方的文化和价值观念在她的身上得到融合,尽管不十分完美,但却令人充满期待。任碧莲试图通过这一人物,表达她对物欲横流的美国社会现状的批判和对“美国梦”的质疑,唤起人们对于亲情的眷恋和真情的渴望。     

Clustering for contingency tables: boxes and partitions

The correspondence analysis (CA) method appears to be an effective tool for analysis of interrelations between rows and columns in two-way contingency data. A discrete version of the method, box clustering, is developed in the paper using an approximation version of the CA model extended to the case when CA factor values are required to be Boolean. Several properties of the proposed SEFIT-BOX algorithm are proved to facilitate interpretation of its output. It is also shown that two known partitioning algorithms (applied within row or column sets only) could be considered as locally optimal algorithms for fitting the model, and extensions of these algorithms to a simultaneous row and column partitioning problem are proposed.