Bayesian life test planning for the Weibull distribution with given shape parameter

This paper describes Bayesian methods for life test planning with Type II censored data from a Weibull distribution, when the Weibull shape parameter is given. We use conjugate prior distributions and criteria based on estimating a quantile of interest of the lifetime distribution. One criterion is based on a precision factor for a credibility interval for a distribution quantile and the other is based on the length of the credibility interval. We provide simple closed form expressions for the relationship between the needed number of failures and the precision criteria. Examples are used to illustrate the results.Received: October 2002 / Revised: March 2004     

EEC双通道健康度评估方法研究

为了解决航空发动机双通道电子控制器(EEC)两个通道均发生故障时如何评估通道健康度,从而选择主控通道的问题,论文提出了基于逆模型计算发动机推力敏感度的方法,量化不同信号故障对发动机推力的影响程度,依据推力敏感度来评估双通道健康度,协助主控通道选择,最终提高系统的安全性。     

养老建筑室内建筑环境的构建——以某市社会养老服务中心为例

养老地产在我国是一项新兴产业,作为该类建筑中的一个重要组成部分——供暖、通风与空气调节工程,其设计合理与否,对于居住环境和老年人身体健康的影响至关重要。设计人员为了力求打造一个更为适合老年人居住的建筑环境,结合具体工程,做了较为细致的探讨。文章对工程设计方案,包括采暖、空调方式,室内空气质量的控制,气流组织,工程材料选择,振动噪声控制,共五大方面,逐一作了介绍。     

电子商务环境下零售商分销渠道的选择

针对电子商务环境下的产品分销渠道,研究了由一个制造商和一个零售商组成的供应链中零售商分销渠道的选择问题。运用主从博弈和Hotelling模型,分别建立了单一线下渠道模型和在同价策略下的双渠道模型,通过对模型的分析,给出了零售商选择不同分销渠道的条件。研究表明:制造商会积极促使零售商选择线上线下双渠道;构建线上渠道的运营成本会影响零售商的渠道选择。研究结果对零售商的渠道选择有一定的指导意义。     

基于行业分布的企业网络信息安全威胁及对策研究

在互联网日益普及的今天,企业越来越重视自身的信息化建设,企业信息化的发展使得接入互联网的企业不断增长,如何保护企业信息安全成为企业发展的关键内容之一。本文采取数理统计及文本分类的方法,对来自某知名黑客论坛的300余万条数据进行分析,通过TF-IDF模型与KNN算法分类思想,得出不同行业的网络信息安全威胁程度,并划分出较低、适中以及较高三类等级。在此基础上,根据行业特点深入剖析了不同行业产生信息安全问题的原因,并提出了相应的改进措施和建议。     

A Bayesian-like estimator of the process capability index Cpmk

Pearn et al. (1992) proposed the capability index C_pmk, and investigated the statistical properties of its natural estimator for stable normal processes with constant mean μ. Chen and Hsu (1995) showed that under general conditions the asymptotic distribution of is normal if μ≠m, and is a linear combination of the normal and the folded-normal distributions if μ=m, where m is the mid-point between the upper and the lower specification limits. In this paper, we consider a new estimator for stable processes under a different (more realistic) condition on process mean, namely, P (μ≥m)=p, 0≤p≤1. We obtain the exact distribution, the expected value, and the variance of under normality assumption. We show that for P (μ≥m)=0, or 1, the new estimator is the MLE of C_pmk, which is asymptotically efficient. In addition, we show that under general conditions is consistent and is asymptotically unbiased. We also show that the asymptotic distribution of is a mixture of two normal distributions. RID="*" ID="*"  The research was partially supported by National Science Council of the Republic of China (NSC-89-2213-E-346-003).     

Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .     

应急物流配送体系研究

分析了应急物流配送的内涵和特性,在此基础上建立了应急物流配送体系,从应急物流配送中心的建立、救灾物资配送方案的选择和物流通道的建设三个层面进行了较为深入的分析和探讨,并对配送工作的加强提出了建议。     

Tales from tails: On the empirical distributions of forecasting errors and their implication to risk

When evaluating the performances of time series extrapolation methods, both researchers and practitioners typically focus on the average or median performance according to some specific error metric, such as the absolute error or the absolute percentage error. However, from a risk-assessment point of view, it is far more important to evaluate the distributions of such errors, and especially their tails. For instance, a lack of normality and symmetry in error distributions can have significant implications for decision making, such as in stock control. Moreover, frequently these distributions can only be constructed empirically, as they may be the result of a computationally-intensive non-parametric approach, such as an artificial neural network. This study proposes an approach for evaluating the empirical distributions of forecasting methods and uses it to assess eleven popular time series extrapolation approaches across two different datasets (M3 and ForeDeCk). The results highlight some very interesting tales from the tails.