军机备件需求量修正的粗糙集方法

本文针对不可量化因素对军机备件需求量的影响,提出了基于粗糙集的备件需求量的修正方法。考虑不可量化因素存在多值性的问题,将不可分辨关系下的经典粗糙集方法拓展成相容关系下的扩展粗糙集方法,通过相容关系下的近似空间获取决策规则,再由决策规则得到修正系数。最后以轮胎类器材为例,说明了修正系数的获取过程。     

基于模糊规划的QFD 系统参数确定方法

针对QFD 系统的内在模糊性,运用带有对称三角形模糊系数的模糊规划理论,提出了一 种确定QFD 系统参数的方法. 并通过工程特性目标值的规范化,定义产品开发总成本函数、工 程特性改进成本函数及改进成本系数等概念,建立了一个QFD 规划模型. 仿真结果表明,该模 型能够帮助开发人员在不确定的、模糊条件下有效确定关联函数及自相关函数,优化顾客需求 的满意水平,确定工程特性目标值,使新开发/ 改进的产品顾客满意度赶上或超过目标市场上 的竞争企业,并满足开发预算约束.     

Pipage Rounding: A New Method of Constructing Algorithms with Proven Performance Guarantee

The paper presents a general method of designing constant-factor approximation algorithms for some discrete optimization problems with assignment-type constraints. The core of the method is a simple deterministic procedure of rounding of linear relaxations (referred to as pipage rounding). With the help of the method we design approximation algorithms with better performance guarantees for some well-known problems including MAXIMUM COVERAGE, MAX CUT with given sizes of parts and some of their generalizations.     

中国股市收益率分布特征研究

应用修正Weibull分布对上海综合指数收益率和深圳成分指数收益率的分布状况进行研究。结果表明:经过简单的移位变换后,上证综指收益率和深成指收益率可完全用修正Weibull分布来刻画;大收益率服从次指数分布,小收益率服从超指数分布;两股指收益率的概率分布存在一些差异,上证综指的波动性大于深成指的波动性;沪深股市收益率的分布在1996年以后发生了较大的变化,其中沪市变化更大。     

New calibration estimator based on two auxiliary variables in stratified sampling

In recent years, calibration estimation has become an important field of research in survey sampling. This paper proposes a new calibration estimator for the population mean in the presence of two auxiliary variables in stratified sampling. The theory of new calibration estimator is given and optimum calibration weights are derived. A simulation study is carried out to performance of the proposed calibration estimator over other existing calibration estimators. The results reveal that the proposed calibration estimators are more efficient than other existing calibration estimators in stratified sampling.     

Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error

In this paper, we develop modified versions of the likelihood ratio test for multivariate heteroskedastic errors-in-variables regression models. The error terms are allowed to follow a multivariate distribution in the elliptical class of distributions, which has the normal distribution as a special case. We derive the Skovgaard-adjusted likelihood ratio statistics, which follow a chi-squared distribution with a high degree of accuracy. We conduct a simulation study and show that the proposed tests display superior finite sample behaviour as compared to the standard likelihood ratio test. We illustrate the usefulness of our results in applied settings using a data set from the WHO MONICA Project on cardiovascular disease.     

Modern likelihood inference for the maximum/minimum of a bivariate normal vector

ABSTRACT

We consider the use of modern likelihood asymptotics in the construction of confidence intervals for the parameter which determines the skewness of the distribution of the maximum/minimum of an exchangeable bivariate normal random vector. Simulation studies were conducted to investigate the accuracy of the proposed methods and to compare them to available alternatives. Accuracy is evaluated in terms of both coverage probability and expected length of the interval. We furthermore illustrate the suitability of our proposals by means of two data sets, consisting of, respectively, measurements taken on the brains of 10 mono-zygotic twins and measurements of mineral content of bones in the dominant and non-dominant arms for 25 elderly women.     

Estimating the population proportion in modified ranked set sampling methods

In this paper, proportion estimators and associated variance estimators are proposed for a binary variable with a concomitant variable based on modified ranked set sampling methods, which are extreme ranked set sampling (ERSS), median ranked set sampling (MRSS), percentile ranked set sampling (Per-RSS) and L ranked set sampling (LRSS) methods. The Monte Carlo simulation study is performed to compare the performance of the estimators based on bias, mean squared error, and relative efficiency for different levels of correlation coefficient, set and cycle sizes under normal and log-normal distributions. Moreover, the study is supported with real data application.     

The Delphi technique: an untapped approach of participatory research

In this article, we describe ways that the Delphi technique can be extended from its more traditional approaches and processes in order to make it a tool for scholars using participatory methods. This innovative proposed approach is called the change-oriented Delphi. We describe this innovative approach using an example from our own work to create solutions to the growth of non-tenure-track faculty in higher education institutions, which is negatively impacting student outcomes.