当代埃及妇女发展问题研究

二战后 ,埃及妇女在教育、就业、参政和健康方面的状况较战前有较大程度改观 :女子入学率、识字率不断提高 ,女大学生所学专业日益广泛 ;妇女就业率增长 ,就业领域拓宽 ;妇女参政比例呈上升趋势 ;生育率、孕产妇死亡率日渐下降 ,妇女预期寿命逐步延长。但埃及妇女在发展过程中依然存在许多问题     

论海湾国家妇女的发展问题

随着经济和社会的发展、开明君主的倡导、媒体的影响,海湾国家妇女在各方面都取得了一定的发展。不过,伊斯兰教传统文化、伊斯兰原教旨主义和家族统治等因素使海湾国家妇女的发展缓慢,并且为未来海湾国家妇女的发展埋下了隐忧。在新世纪,海湾国家妇女的发展需要她们自己不懈地努力,需要海湾各国政府为本国妇女的发展提供必要的支持,需要建立男女"伙伴与合作关系",还需要考虑社会不同阶层妇女的实际情况。     

多维互动:族际政治整合机制研究

多维互动是族际政治整合的一种重要机制,政府、社会组织、族员三者互动的结构、特点、方式、内容构成了这种机制的基本框架。其具有认知、理解、信任、包容等功能,这些功能促进了各族员由民族认同到国家认同的转向。因此,建构族际政治整合多维互动机制是实现各族员和谐共处、共同发展的政治保障。     

Risk aggregation with dependence and overdispersion based on the compound Poisson INAR(1) process

Abstract

This paper considers an extension of the classical discrete time risk model for which the claim numbers are assumed to be temporal dependence and overdispersion. The risk model proposed is based on the first-order integer-valued autoregressive (INAR(1)) process with discrete compound Poisson distributed innovations. The explicit expression for the moment generating function of the discounted aggregate claim amount is derived. Some numerical examples are provided to illustrate the impacts of dependence and overdispersion on related quantities such as the stop-loss premium, the value at risk and the tail value at risk.     

Independence test in high-dimension using distance correlation and power enhancement technique

Abstract

This paper is concerned with independence test in high-dimension. A new test statistic is proposed with two terms: one is based on the modified distance correlation statistic, the other is constructed to enhance the power under sparse alternatives. Asymptotic properties of the test statistic are discussed under some regular conditions. The finite-sample simulations exhibit its superiority over some existing procedures. Finally, a real data example illustrates the proposed test.     

Interval estimation for conformance proportions of multiple quality characteristics

A conformance proportion is an important and useful index to assess industrial quality improvement. Statistical confidence limits for a conformance proportion are usually required not only to perform statistical significance tests, but also to provide useful information for determining practical significance. In this article, we propose approaches for constructing statistical confidence limits for a conformance proportion of multiple quality characteristics. Under the assumption that the variables of interest are distributed with a multivariate normal distribution, we develop an approach based on the concept of a fiducial generalized pivotal quantity (FGPQ). Without any distribution assumption on the variables, we apply some confidence interval construction methods for the conformance proportion by treating it as the probability of a success in a binomial distribution. The performance of the proposed methods is evaluated through detailed simulation studies. The results reveal that the simulated coverage probability (cp) for the FGPQ-based method is generally larger than the claimed value. On the other hand, one of the binomial distribution-based methods, that is, the standard method suggested in classical textbooks, appears to have smaller simulated cps than the nominal level. Two alternatives to the standard method are found to maintain their simulated cps sufficiently close to the claimed level, and hence their performances are judged to be satisfactory. In addition, three examples are given to illustrate the application of the proposed methods.     

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.