Extended scaled prediction variance optimality for modified central composite design

Robust parameter designs (RPDs) enable the experimenter to discover how to modify the design of the product to minimize the effect due to variation from noise sources. The aim of this article is to show how this amount of work can be reduced under modified central composite design (MCCD). We propose a measure of extended scaled prediction variance (ESPV) for evaluation of RPDs on MCCD. Using these measures, we show that we can check the error or bias associated with estimating the model parameters and suggest the values of α recommended for MCCS under minimum ESPV.     

A new confidence interval in measurement error model with the reliability ratio known

For the slope parameter of the measurement error model with the reliability ratio known, this article constructs a fiducial generalized confidence interval (FGCI) which is proved to have correct asymptotic coverage. Simulation results demonstrate that the FGCI often outperforms the existing intervals in terms of empirical coverage probability, average interval length, and false parameter coverage rate. Two examples are also provided to illustrate our approach.     

播音实验室声学要求及处理

播音实验室声学要求及处理主要从隔音处理、混响时间方面考虑，结合湛江师范学院播音实验室的建设从声学设计要求方面作了简单介绍。     

农村社区建设的参数分析

农村社区建设应坚持科学发展观,按照"生产发展、生活宽裕、乡风文明、村容整洁、管理民主"的社会主义新农村建设目标要求,建设人与自然和谐相处的村民"宜居社区"和"精神家园"。社区建设涵盖经济收入指数、人居环境指数、居民幸福指数、社区参与指数、平安康乐指数、福利保障指数、社区归属感等参数。     

“三驾马车”与福建经济增长的动态关系——基于时变参数状态空间模型的实证研究

基于福建省地区生产总值、消费、投资和净出口数据,构建了揭示"三驾马车"与福建经济增长间动态关系的变参数状态空间模型,分析了其动态变化的轨迹与趋势。实证结果表明:"三驾马车"对福建经济增长的拉动作用具有明显的阶段性特征,虽然投资的拉动作用一直超过消费和净出口,但2005年后消费的拉动作用在稳步增强而投资的拉动作用在逐年减弱,说明福建经济对投资的依赖性正在下降,经济转型早已开始并且趋势稳定,正在稳步进入可持续的发展轨道,政府无需做过多的干预。     

小型变流量电磁泵的结构优化设计

本文在介绍电磁泵的结构组成的基础上,详细介绍了采用复合形法对电磁泵进行优化设计的具体步骤。     

众数就是位置平均数及其他——与范赞成先生关于《众数之误》商榷

文章对<众数之误>一文不准确之处进行了分析,指出众数就是位置平均数,现行统计教材中关于众数的内容基本正确,并希望与该文作者及读者进行交流.     

应用同伦正则化算法反演二维溶质运移模型中的弥散系数

利用同伦正则化算法探讨了二维对流弥散方程的依赖空间变量的弥散系数反演问题.讨论了初始迭代值、数值微分步长、以及收敛精度对算法实现的影响.数值模拟表明,同伦正则化算法对于此类参数反演问题是一种有效的方法.     

On the computation of the noncentral <Emphasis Type="Italic">F</Emphasis> and noncentral beta distribution

Unfortunately many of the numerous algorithms for computing the comulative distribution function (cdf) and noncentrality parameter of the noncentral F and beta distributions can produce completely incorrect results as demonstrated in the paper by examples. Existing algorithms are scrutinized and those parts that involve numerical difficulties are identified. As a result, a pseudo code is presented in which all the known numerical problems are resolved. This pseudo code can be easily implemented in programming language C or FORTRAN without understanding the complicated mathematical background. Symbolic evaluation of a finite and closed formula is proposed to compute exact cdf values. This approach makes it possible to check quickly and reliably the values returned by professional statistical packages over an extraordinarily wide parameter range without any programming knowledge. This research was motivated by the fact that a very useful table for calculating the size of detectable effects for ANOVA tables contains suspect values in the region of large noncentrality parameter values compared to the values obtained by Patnaik’s 2-moment central-F approximation. The cause is identified and the corrected form of the table for ANOVA purposes is given. The accuracy of the approximations to the noncentral-F distribution is also discussed. The authors wish to thank Mr. Richárd Király for his preliminary work. The authors are grateful to the Editor and Associate Editor of STCO and the unknown reviewers for their helpful suggestions.     

The umvue and bayes estimate of reliability of mixed failure time distribution

We study the reliability estimates of the non-standard mixture of degenerate (degenerated at zero) and exponential distributions. The Uniformly Minimum Variance Unbiased Estimator (UMVUE) and Bayes estimator of the reliability for some selective prior when the mixing proportion is known and unknown are derived. The Bayes risk is computed for each Bayes estimator of the reliability. A simulated study is carried out to assess the performance of the estimators alongwith the true and Maximum Likelihood Estimate (MLE) of the reliability. An example from Vannman (1991) is also discussed at the end of the paper.