Comparison of Cramer–Rao lower bounds of variances for at least equal protection of respondents

In this paper, a new randomized response model is proposed, which is shown to have a Cramer–Rao lower bound of variance that is lower than the Cramer–Rao lower bound of variance suggested by Singh and Sedory at equal protection or greater protection of respondents. A new measure of protection of respondents in the setup of the efficient use of two decks of cards, because of Odumade and Singh, is also suggested. The developed Cramer–Rao lower bounds of variances are compared under different situations through exact numerical illustrations. Survey data to estimate the proportion of students who have sometimes driven a vehicle after drinking alcohol and feeling over the legal limit are collected by using the proposed randomization device and then analyzed. The proposed randomized response technique is also compared with a black box technique within the same survey. A method to determine minimum sample size in randomized response sampling based on a small pilot survey is also given.     

On the optimum number of levels in the one-way model with random effects

The optimal number of levels is studied for the one-way random model with normally distributed effects. The optimum criteria used are based on the variances of the traditional analysis of variance estimators of the variance components. Exact solutions are compared to earlier results based on lower bounds of the sampling variances. Comparisons are also made to the large-sample variances of the estimates based on restricted maximum likelihood. Received February 2002     

An alternative model for the analysis of variance with random effects

The standard model for the analysis of variance with random effects implies, for the case of two independent variables, that single effects must be tested not against the error, but against the interaction mean squares. This causes, in comparison with the fixed effects AV, a considerable loss of test power, particularly for the 2 × 2 table. An alternative modelling of the interaction effect is proposed which completely avoids the loss of power.     

The analysis of unbalanced linear models with variance components

Statistical inference for fixed effects, random effects and components of variance in an unbalanced linear model with variance components will be discussed. Variance components will be estimated by Restricted Maximum Likelihood. Iterative procedures for computing the estimates, such as Fisher scoring and the EM-algorithm, are described.     

Natural estimation of variances in a general finite discrete spectrum linear regression model

The method of “natural” estimation of variances in a general (orthogonal or nonorthogonal) finite discrete spectrum linear regression model of time series is suggested. Using geometrical language of the theory of projectors a form and properties of the estimators are investigated. Obtained results show that in describing the first and second moment properties of the new estimators the central role plays a matrix known in linear algebra as the Schur complement. Illustrative examples with particular regressors demonstrate direct applications of the results.     

从政治功能浅析美国两类跨国公司进入中国市场的方式与阶段

本文从政治功能视角分析中国政府对美国制造型跨国公司与跨国传媒集团两类跨国公司进入中国市场截然不同态度,和两类跨国公司相对应而采取的进入中国市场的不同方式和阶段。     

从政治功能浅析美国两类跨国公司进入中国市场的方式与阶段

本文从政治功能视角分析中国政府对美国制造型跨国公司与跨国传媒集团两类跨国公司进入中国市场截然不同态度 ,和两类跨国公司相对应而采取的进入中国市场的不同方式和阶段。     

On random fuzzy variables of second order and their application to linear statistical inference with fuzzy data

This paper summarizes some results on random fuzzy variables with existing expectation and variance, called random fuzzy variables of second order. Using the Frechét-principle and – via support functions – the embedding of convex fuzzy sets into a Banach space of functions it especially presents a unified view on expectation and variance of random fuzzy variables. These notions are applied in developing linear statistical inference with fuzzy data. Detailed investigations are presented concerning best linear unbiased estimation in linear regression models with fuzzy observations. Received: November 1999     

信息技术环境下会计模式的新发展

信息技术环境下,传统会计模式已不能满足企业发展的需求。文章通过与传统会计模式进行比较,对未来会计模式的发展趋势作出了展望。     

高职理实一体化实训室环保与安全管理探析

高职理实一体化实训室是培养具有实践创新能力的高素质人才的场所,理实一体化实训室的环保与安全管理是教学、科研工作正常开展的前提。结合常州工程职业技术学院三年来生物理实一体化实训室的工作实践,从基础设施建设、完善规章制度、健全运行机制、安全教育培训、个人安全防护、规范性操作、危化品管理、实验废弃物处理等方面对生物理实一体化实训室的环保与安全管理进行了总结探讨。     

Asymptotically optimal nonparametric one- and two-way analysis of variance tests for the log linear model under censoring

We considerr ×c populations with failure ratesλ _ij(t) satisfying the condition

如何利用Internet完成顾客忠诚信息的收集与测评

顾客忠诚直接影响了企业获取利润的持久性和扩展能力．如何借助发达的网络和计算机技术及时获取顾客的忠诚度，并据此采取相应营销战略，已经成为企业十分关注的问题。本文构建的基于Internet的顾客忠诚度信息收集与测评系统模型很好地解决了这一问题；同时构建了移动行业的顾客忠诚度模型并设计了相应的指标体系借以说明该系统的应用。     

对影响中国外汇储备规模因素的实证研究——以1985年～2005年数据为例

2006年末,我国外汇储备已突破1万亿美元,外汇储备规模成为政府和学术界关注的焦点。文中从实证的角度出发,建立了双对数计量经济模型,运用EVIEWS软件分析了影响中国外汇储备规模的多种因素,确定国外债务还本付息、进口与汇率是影响我国外汇储备规模的最重要因素,得出回归方程,为预测和制定相关的政策提供一定的依据。     

Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification

Since the 1990s, the Akaike Information Criterion (AIC) and its various modifications/extensions, including BIC, have found wide applicability in econometrics as objective procedures that can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences, primarily because their choice within a prespecified family of models (a) assumes away the problem of model validation, and (b) ignores the relevant error probabilities. This paper argues for a return to the original statistical model specification problem, as envisaged by Fisher (1922), where the task is understood as one of selecting a statistical model in such a way as to render the particular data a truly typical realization of the stochastic process specified by the model in question. The key to addressing this problem is to replace trading goodness-of-fit against parsimony with statistical adequacy as the sole criterion for when a fitted model accounts for the regularities in the data.