A Study to Improve the Method of Ascertaining Attribute Weight Based on Rough Sets Theory

There are some shortages to ascertain attribute weight based on rough set in current studies. In this paper, attrib- ute importance represented by rough set is studied deeply. Aiming at the existing problems, algebra presentation of rough sets is proved to be more comprehensive than its information presentation, then a new method of ascertaining attribute weigh is put forward based on rough set conditional entropy. Finally, it is shown that the new method is more reasonable than the old one by an example.     

Intercandidate agenda-setting in presidential elections: Issue and attribute agendas in the 2004 campaign

This study examined the role of political public relations in the process of intercandidate agenda-setting. Specifically, a content analysis of news releases, political speeches, and issue platform statements was conducted to assess the salience of issues and attributes in the 2004 presidential election from the Bush, Kerry, and Nader campaigns. While modest evidence for intercandidate agenda-setting associations regarding issue salience was obtained, more robust support was detected for attribute salience relationships. In light of these findings, the theoretical and practical implications for political public relations are discussed.     

经济新常态下混合所有制的改革方式与推进要点--基于正和博弈的视域

十八届三中全会以来,混合所有制被视为推动国资国企改革的加速器。而混合所有制并非新提法,党的十四届三中全会就已提出混合经济的思想。文章认为当下重提混合所有制是为了巩固基本经济制度,促进非公有制经济发展,让国民共享经济发展成果。混合所有制不是“国退民进”、或“国进民退”的零和博弈,而是可以实现“国民共进”的正和博弈。在经济新常态的背景下,深化混合所有制改革是不断提高国有经济的活力、控制力、影响力的重要手段,应用正和博弈的思维看待混合所有制改革,采取渐进分类分拆的方式推进混合所有制改革,而改革的关键点在于建立规范化的法人治理结构。     

A Parametric Bootstrap Test for Two-Way ANOVA Model Without Interaction Under Heteroscedasticity

In this article we consider the two-way ANOVA model without interaction under heteroscedasticity. For the problem of testing equal effects of factors, we propose a parametric bootstrap (PB) approach and compare it with existing the generalized F (GF) test. The Type I error rates and powers of the tests are evaluated using Monte Carlo simulation. Our studies show that the PB test performs better than the GF test. The PB test performs very satisfactorily even for small samples while the GF test exhibits poor Type I error properties when the number of factorial combinations or treatments goes up. It is also noted that the same tests can be used to test the significance of random effect variance component in a two-way mixed-effects model under unequal error variances.     

Calculation of the expected lifetime lost due to an extra risk

Methods are given for estimating the average years of life lost when a person is discovered to be at risk from an extra hazard. The methods use the probability per year of the extra risk striking, and the mean and standard deviation of lifetime in the absence of the risk. The formulae are simple enough that only a hand‐held calculator is needed.     

CUSUM Control Charts for Multivariate Poisson Distribution

A cumulative sum control chart for multivariate Poisson distribution (MP-CUSUM) is proposed. The MP-CUSUM chart is constructed based on log-likelihood ratios with in-control parameters, Θ₀, and shifts to be detected quickly, Θ₁. The average run length (ARL) values are obtained using a Markov Chain-based method. Numerical experiments show that the MP-CUSUM chart is effective in detecting parameter shifts in terms of ARL. The MP-CUSUM chart with smaller Θ₁ is more sensitive than that with greater Θ₁ to smaller shifts, but more insensitive to greater shifts. A comparison shows that the proposed MP-CUSUM chart outperforms an existing MP chart.     

A Lower Bound for the Wrap-around L2-discrepancy on Combined Designs of Mixed Two- and Three-level Factorials

The objective of this article is to study the issue of employing the uniformity criterion measured by wrap-around L₂-discrepancy to assess the optimal foldover plans. For mixed two- and three-level fractional factorials as the original designs, general foldover plan and combined design under a foldover plan are defined, and the equivalence between any foldover plan and its complementary foldover plan is investigated. A lower bound of wrap-around L₂-discrepancy of combined designs under a general foldover plan is obtained, which can be used as a benchmark for searching optimal foldover plans. Moreover, it also provides a theoretical justification for optimal foldover plans in terms of uniformity criterion.     

Assessing the performance of variational methods for mixed logistic regression models

We present a variational estimation method for the mixed logistic regression model. The method is based on a lower bound approximation of the logistic function [Jaakkola, J.S. and Jordan, M.I., 2000, Bayesian parameter estimation via variational methods. Statistics & Computing, 10, 25–37.]. Based on the approximation, an EM algorithm can be derived that results in a considerable simplification of the maximization problem in that it does not require the numerical evaluation of integrals over the random effects. We assess the performance of the variational method for the mixed logistic regression model in a simulation study and an empirical data example, and compare it to Laplace's method. The results indicate that the variational method is a viable choice for estimating the fixed effects of the mixed logistic regression model under the condition that the number of outcomes within each cluster is sufficiently high.     

A tolerance interval approach for assessment of agreement in method comparison studies with repeated measurements

This paper generalizes the tolerance interval approach for assessing agreement between two methods of continuous measurement for repeated measurement data—a common scenario in applications. The repeated measurements may be longitudinal or they may be replicates of the same underlying measurement. Our approach is to first model the data using a mixed model and then construct a relevant asymptotic tolerance interval (or band) for the distribution of appropriately defined differences. We present the methodology in the general context of a mixed model that can incorporate covariates, heteroscedasticity and serial correlation in the errors. Simulation for the no-covariate case shows good small-sample performance of the proposed methodology. For the longitudinal data, we also describe an extension for the case when the observed time profiles are modelled nonparametrically through penalized splines. Two real data applications are presented.