MUX級联网络的組合設計

利用MUX级联网络实现多变量逻辑函数时,为求得最简的级联系统,本文提出了利用剩余函数立方图求取变量划分的快速方法。该法无需借助卡诺图,也不需要进行复杂的运算。结果表明,该法行之有效而且十分方便。     

汽液两相喷嘴中临界流的简化数学模型

本文介绍了考虑汽液两相间的传热、传质与动量交换后,汽液两相喷嘴中临界质量流速的简化数学模型,并根据他人试验结果所作的近似假设,提供了喷嘴中汽液两相流的临界压比计算式。     

改进的投影寻踪分类模型及其在区域经济评价中的应用

作为多元数据的一种分析方法,投影寻踪分类模型已被一些研究者应用到实践中,并取得了良好的效果.然而,投影寻踪分类模型没有严格意义上的分类标准.通过引入有序样本聚类法,可以对投影寻踪分类模型得到的一维投影值进行客观分类.根据改进的模型,对江苏省区域经济的发展进行了综合评价,结果表明:改进的投影寻踪分类模型切实可行,为多元数据分类提供了新途径.     

个人教育收益率的估计与比较: 一个半参数方法

 本文运用一种变系数部分线性模型扩展了传统的明瑟人力资本收入函数,并提出了对明瑟函数中“平行性”假设的一种检验方法,以分析个人教育收益率如何受到工龄等因素的影响。通过对1991、2000以及2004等年度国家统计局城镇居民收入调查数据的分析,揭示出近二十年来我国城镇居民中不同工龄的人们的教育收益率存在明显区别,其中人教育收益率最高的始终是在1980年代中后期参加工作的群体。对导致我国教育收益率这种特殊现象的原因作了分析。     

Exact average coverage probabilities and confidence coefficients of confidence intervals for discrete distributions

For a confidence interval (L(X),U(X)) of a parameter θ in one-parameter discrete distributions, the coverage probability is a variable function of θ. The confidence coefficient is the infimum of the coverage probabilities, inf  _θ P _θ (θ∈(L(X),U(X))). Since we do not know which point in the parameter space the infimum coverage probability occurs at, the exact confidence coefficients are unknown. Beside confidence coefficients, evaluation of a confidence intervals can be based on the average coverage probability. Usually, the exact average probability is also unknown and it was approximated by taking the mean of the coverage probabilities at some randomly chosen points in the parameter space. In this article, methodologies for computing the exact average coverage probabilities as well as the exact confidence coefficients of confidence intervals for one-parameter discrete distributions are proposed. With these methodologies, both exact values can be derived.     

Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires

There has been increasing use of quality-of-life (QoL) instruments in drug development. Missing item values often occur in QoL data. A common approach to solve this problem is to impute the missing values before scoring. Several imputation procedures, such as imputing with the most correlated item and imputing with a row/column model or an item response model, have been proposed. We examine these procedures using data from two clinical trials, in which the original asthma quality-of-life questionnaire (AQLQ) and the miniAQLQ were used. We propose two modifications to existing procedures: truncating the imputed values to eliminate outliers and using the proportional odds model as the item response model for imputation. We also propose a novel imputation method based on a semi-parametric beta regression so that the imputed value is always in the correct range and illustrate how this approach can easily be implemented in commonly used statistical software. To compare these approaches, we deleted 5% of item values in the data according to three different missingness mechanisms, imputed them using these approaches and compared the imputed values with the true values. Our comparison showed that the row/column-model-based imputation with truncation generally performed better, whereas our new approach had better performance under a number scenarios.     

Quasi-minimax estimation in the general linear regression model

This paper is mainly concerned with minimax estimation in the general linear regression model y=Xβ+ε$y=X\beta +\epsilon$ under ellipsoidal restrictions on the parameter space and quadratic loss function. We confine ourselves to estimators that are linear in the response vector y  . The minimax estimators of the regression coefficient β$\beta$ are derived under homogeneous condition and heterogeneous condition, respectively. Furthermore, these obtained estimators are the ridge-type estimators and mean dispersion error (MDE) superior to the best linear unbiased estimator b=(X^′W^-1X)^-1X^′W^-1y$b=(X^{\prime }{W}^{-1}X{)}^{-1}{X}^{\prime }{W}^{-1}y$ under some conditions.     

Nonparametric estimation of the shape function in a Gamma process for degradation data

The author considers estimation under a Gamma process model for degradation data. The setting for degradation data is one in which n independent units, each with a Gamma process with a common shape function and scale parameter, are observed at several possibly different times. Covariates can be incorporated into the model by taking the scale parameter as a function of the covariates. The author proposes using the maximum pseudo‐likelihood method to estimate the unknown parameters. The method requires usage of the Pool Adjacent Violators Algorithm. Asymptotic properties, including consistency, convergence rate and asymptotic distribution, are established. Simulation studies are conducted to validate the method and its application is illustrated by using bridge beams data and carbon‐film resistors data. The Canadian Journal of Statistics 37: 102‐118; 2009 © 2009 Statistical Society of Canada     

Estimation in capture–recapture models when covariates are subject to measurement errors and missing data

For capture–recapture models when covariates are subject to measurement errors and missing data, a set of estimating equations is constructed to estimate population size and relevant parameters. These estimating equations can be solved by an algorithm similar to the EM algorithm. The proposed method is also applicable to the situation when covariates with no measurement errors have missing data. Simulation studies are used to assess the performance of the proposed estimator. The estimator is also applied to a capture–recapture experiment on the bird species Prinia flaviventris in Hong Kong. The Canadian Journal of Statistics 37: 645–658; 2009 © 2009 Statistical Society of Canada     

中美石油安全水平对经济增长影响的对比研究——基于灰色关联分析

为科学地评价比较中美石油安全水平对经济增长的影响程度,文章采用主成分分析方法,选取采储比水平、储量接替率、消费弹性系数、原油价格波动系数、对外依存度和石油占一次能源消费比重等6个要素指标,构成一个新的石油安全指标评价体系,并利用灰色关联方法比较分析了不同时间段内中美两国的石油安全水平与经济增长之间的关联度,得出自21世纪以来,美国经济发展对石油安全水平的依赖程度要远大于中国的结论。