产品优化设计的用户满意模型

研究品质功能展开的产品优化设计问题. 考虑产品设计过程中的设计预算和非精确性, 引进计划可达水平、实际计划水平等概念,提出产品优化设计的用户满意模型及参数规划求解 方法. 此方法给出满足设计预算的不同可能性条件下的设计方案,供产品设计负责人做出不同 的方案选择,更能反映设计过程的实际情况.     

Adult Mortality Five Years after a Natural Disaster

Exposure to extreme events has been hypothesized to affect subsequent mortality because of mortality selection and scarring effects of the event itself. We examine survival at and in the five years after the 2004 Indian Ocean earthquake and tsunami for a population‐representative sample of residents of Aceh, Indonesia who were differentially exposed to the disaster. For this population, the dynamics of selection and scarring are a complex function of the degree of tsunami impact in the community, the nature of individual exposures, age at exposure, and gender. Among individuals from tsunami‐affected communities we find evidence for positive mortality selection among older individuals, with stronger effects for males than for females, and that this selection dominates any scarring impact of stressful exposures that elevate mortality. Among individuals from other communities, where mortality selection does not play a role, there is evidence of scarring with property loss associated with elevated mortality risks in the five years after the disaster among adults age 50 or older at the time of the disaster.     

Survival analysis with incomplete genetic data

Genetic data are now collected frequently in clinical studies and epidemiological cohort studies. For a large study, it may be prohibitively expensive to genotype all study subjects, especially with the next-generation sequencing technology. Two-phase sampling, such as case-cohort and nested case-control sampling, is cost-effective in such settings but entails considerable analysis challenges, especially if efficient estimators are desired. Another type of missing data arises when the investigators are interested in the haplotypes or the genetic markers that are not on the genotyping platform used for the current study. Valid and efficient analysis of such missing data is also interesting and challenging. This article provides an overview of these issues and outlines some directions for future research.     

Boxplot-Based Outlier Detection for the Location-Scale Family

Boxplots are among the most widely used exploratory data analysis (EDA) tools in statistical practice. Typical applications of boxplots include eliciting information about the underlying distribution (shape, location, etc.) as well as identifying possible outliers. This article focuses on a modification using a type of lower and upper fences similar in concept to those used in a traditional boxplot; however, instead of constructing the upper and lower fences using the upper and lower quartiles, respectively, and a multiple of the interquartile range (IQR), multiples of the upper and the lower semi-interquartile ranges (SIQR), respectively, measured from the sample median, are used. Any observation beyond the proposed fences is labeled a potential outlier. An exact expression for the probability that at least one sample observation is wrongly classified as an outlier, the so-called “some-outside rate per sample” (Hoaglin et al. (1986)), is derived for the family of location-scale distributions and is used in the determination of the fence constants. Tables for the fence constants are provided for a number of well-known location-scale distributions along with some illustrations with data; the performance of the outlier detection rule is explored in a simulation study.     

Missing Data Mechanisms for Analysing Longitudinal Data with Incomplete Observations in Both Responses and Covariates

Missing observations in both responses and covariates arise frequently in longitudinal studies. When missing data are missing not at random, inferences under the likelihood framework often require joint modelling of response and covariate processes, as well as missing data processes associated with incompleteness of responses and covariates. Specification of these four joint distributions is a nontrivial issue from the perspectives of both modelling and computation. To get around this problem, we employ pairwise likelihood formulations, which avoid the specification of third or higher order association structures. In this paper, we consider three specific missing data mechanisms which lead to further simplified pairwise likelihood (SPL) formulations. Under these missing data mechanisms, inference methods based on SPL formulations are developed. The resultant estimators are consistent, and enjoy better robustness and computation convenience. The performance is evaluated empirically though simulation studies. Longitudinal data from the National Population Health Survey and Waterloo Smoking Prevention Project are analysed to illustrate the usage of our methods.     

建筑施工企业质量损失成本源的分析研究

质量损失成本源分析 ,是企业质量管理工作的重要组成部分 ,对企业进行质量改进、减少质量损失成本具有重要的作用。本文结合建筑施工企业质量损失成本源分析的特点 ,对质量损失成本源分析工作程序和方法进行研究     

对高职《高等数学》教学的探讨

高数教育在大学教育中的三个作用是:掌握数学工具,培养理性思维和接受美感熏陶。高职数学教育思想的转变,内容的新认识,数学教学方法,尝试口头报告式作业方式,数学实验辅助教学。     

A Simple Data Transformation for Estimating Benchmark Doses in Developmental Toxicity Experiments

Developmental anomalies induced by toxic chemicals may be identified using laboratory experiments with rats, mice or rabbits. Multinomial responses of fetuses from the same mother are often positively correlated, resulting in overdispersion relative to multinomial variation. In this article, a simple data transformation based on the concept of generalized design effects due to Rao-Scott is proposed for dose-response modeling of developmental toxicity. After scaling the original multinomial data using the average design effect, standard methods for analysis of uncorrected multinomial data can be applied. Benchmark doses derived using this approach are comparable to those obtained using generalized estimating equations with an extended Dirichlet-trinomial covariance function to describe the dispersion of the original data. This empirical agreement, coupled with a large sample theoretical justification of the Rao-Scott transformation, confirms the applicability of the statistical methods proposed in this article for developmental toxicity risk assessment.     

A multivariate extension of poisson's theorem

For n ≥ 1, let X_nl,…, X_nn be independent integer-valued random variables, and define S_n = X_nl+···+X_nn. In a recent paper, we obtained a simple proof for the convergence of the distribution of S_n to a Poisson distribution under very general conditions. In this paper, we extend that result to the multidimensional case.