Risk Assessment for Hospital-Acquired Diseases: A Risk-Theory Approach

We introduce a new approach to hospital-acquired disease risk assessment from public health databases. In a spirit similar to actuarial risk theory, we define an adjustment coefficient that can quantify the risk associated with a hospital department, allowing comparisons of similar departments. The adjustment coefficient characterizes the tail of the distribution of the total patient length of stay in a department before the first disease event occurs. We show that this coefficient is the solution of a Lundberg-like equation, and we provide a nonparametric estimation procedure for this measure, based on a Cramér-Lundberg approximation for the tail of the distribution. Using simulations, we provide evidence of the robustness of the approximation to various individual risk models. In addition, we illustrate the relevance of this approach by evaluating the risk associated with a standard patient safety indicator in 20 hospitals of southeastern France.     

On prediction from the location-scale model with equi correlated response

The location-scale model with equi-correlated responses is discussed. The structure of the location-scale model is utilised to genera-te the prediction distribution of a future response and that of a set of future responses. The method avoids the integration procedures usually involved in derivation of prediction distributions and yields results same as those obtained by the Bayes method with the vague prior distribution* Finally the re-suits have been specialised to cover the case of the normal intra-class model.     

A property of coefficients of variation for ordered bivariate log-normal variables

This paper considers the maximum and minimum of a pair of log-normal variables with equal mean. It shows that either order statistic has a smaller coefficient of variation than the two original log-normal variables provided the latter are of equal variance. When the variances are unequal, as the variance ratio increases, the minimum (maximum), has a smaller coefficient of variation if the correlation coefficient of the log-normal variables is small (small) and the variances are large (small).     

达里厄垂直轴风力机叶片螺旋变异优化研究

针对传统达里厄( Darrieus)直叶片垂直轴风力机在运行过程中出现叶片动转矩周期波动性大,动转矩系数曲线 震荡剧烈,造成对风轮旋转主轴的强烈冲击及风力机功率输出不稳定等问题,文章提出对Darrieus垂直轴风力机传统直 叶片进行螺旋扭曲变异设计,以改善风力机叶片的动转矩输出性能。结合SolidWorks和MATLAB完成风力机模型的三 维参数化建模,在流体仿真软件FLUENT中完成模型的数值模拟仿真计算。通过螺旋扭曲角的单因素试验验证了变异 设计叶片输出的动转矩性能周期波动性降低,平均动转矩得到提高,并确定螺旋扭曲角的优化区间。文章构建了风力机 系统模型建立与仿真体系,采取螺旋扭曲变异设计,改善了风力机叶片输出的动转矩性能,初步确定合理的螺旋扭曲角 分布范围为：70°~ ll0°。     

Factor screening in nonregular two-level designs based on projection-based variable selection

In this paper, we focus on the problem of factor screening in nonregular two-level designs through gradually reducing the number of possible sets of active factors. We are particularly concerned with situations when three or four factors are active. Our proposed method works through examining fits of projection models, where variable selection techniques are used to reduce the number of terms. To examine the reliability of the methods in combination with such techniques, a panel of models consisting of three or four active factors with data generated from the 12-run and the 20-run Plackett–Burman (PB) design is used. The dependence of the procedure on the amount of noise, the number of active factors and the number of experimental factors is also investigated. For designs with few runs such as the 12-run PB design, variable selection should be done with care and default procedures in computer software may not be reliable to which we suggest improvements. A real example is included to show how we propose factor screening can be done in practice.     

中国快递业发展的区域不平衡性测度研究

选取大陆31个省份2007—2014年样本数据,分别测算三区域、八区域分组下快递业发展的不平衡性及极化趋势。研究结果表明:中国快递业发展存在较强的区域不平衡性,且这种不平衡性还呈现不断加大趋势;东中西快递业发展不平衡性明显,总体呈现东部强中西部弱的特点,基尼系数分解结果显示,东中西组间差异为不平衡性贡献了70%以上的份额,同时东部和西部地区内部也存在相当程度的不平衡性;八区域不平衡性也非常明显,总体呈现沿海强内陆弱、东强西弱、南强北弱的基本格局,组间差异贡献了88%左右的份额,就区域内而言,南部沿海和西北地区不平衡性较强,东部沿海、长江中游及东北地区则较为平衡;三区域及八区域分组下快递业不平衡发展均呈现出不断增强的极化趋势。     

Asymptotic distribution of regression correlation coefficient for Poisson regression model

This study treats an asymptotic distribution for measures of predictive power for generalized linear models (GLMs). We focus on the regression correlation coefficient (RCC) that is one of the measures of predictive power. The RCC, proposed by Zheng and Agresti is a population value and a generalization of the population value for the coefficient of determination. Therefore, the RCC is easy to interpret and familiar. Recently, Takahashi and Kurosawa provided an explicit form of the RCC and proposed a new RCC estimator for a Poisson regression model. They also showed the validity of the new estimator compared with other estimators. This study discusses the new statistical properties of the RCC for the Poisson regression model. Furthermore, we show an asymptotic normality of the RCC estimator.     

Stochastic correlation coefficient ensembles for variable selection

In this paper, we propose a novel Max-Relevance and Min-Common-Redundancy criterion for variable selection in linear models. Considering that the ensemble approach for variable selection has been proven to be quite effective in linear regression models, we construct a variable selection ensemble (VSE) by combining the presented stochastic correlation coefficient algorithm with a stochastic stepwise algorithm. We conduct extensive experimental comparison of our algorithm and other methods using two simulation studies and four real-life data sets. The results confirm that the proposed VSE leads to promising improvement on variable selection and regression accuracy.     

Pooled Cross-Sectional and Time Series Data: A Survey of Current Statistical Methodology

A data base that provides a multivariate statistical history for each of a number of individual entities is called a pooled cross-sectional and time series data base in the econometrics literature. In marketing and survey literature the terms panel data or longitudinal data are often used. In management science a convenient term might be management data base. Such a data base provides a particularly rich environment for statistical analysis. This article reviews methods for estimating multivariate relationships particular to each individual entity and for summarizing these relationships for a number of individuals. Inference to a larger population when the data base is viewed as a sample is also considered.