资本利润率趋向下降规律的启示

劳动社会生产力的发展致使在资本主义商品经济中有资本利润率趋向下降的规律,文中基于相同的原因又得出了在商品经济社会中也存在着工人生活必需品扩大的规律,并通过对于主要资本主义国家经济史的考察,验证了这一规律的正确性。最后,本文运用OLS法对我国国民收入结构进行线性回归分析发现：增加低收入者、工人阶层的工资收入,自觉运用工人生活必需品扩大规律,是当前破解宏观经济问题的关键。     

资本扩张、资本逻辑悖论与科学发展观

剩余价值一旦转化为资本,投入社会生产系统内部而使其得到增值,就会使整个经济系统不断扩张。这种资本扩张给社会发展提供了强大动力,也产生了深层危机,它引起社会经济系统、社会结构、资源环境和人的全面发展等方面的冲突,使资本无法扩张,形成“资本逻辑悖论”。科学发展观是实现这种价值复归的路径选择,是对资本扩张产生种种危机历史之谜的解答。     

扩招后高校课程表的编排、管理的优化

课程表是学校每学期教学计划的具体体现,是高等学校日常教学活动的“指挥调度表”,是教学任务能够很好完成的重要保证。扩招后如何优化高校课程表的编排和管理,是关乎教学运行的关键。     

A ‘nondecimated’ lifting transform

Classical nondecimated wavelet transforms are attractive for many applications. When the data comes from complex or irregular designs, the use of second generation wavelets in nonparametric regression has proved superior to that of classical wavelets. However, the construction of a nondecimated second generation wavelet transform is not obvious. In this paper we propose a new ‘nondecimated’ lifting transform, based on the lifting algorithm which removes one coefficient at a time, and explore its behavior. Our approach also allows for embedding adaptivity in the transform, i.e. wavelet functions can be constructed such that their smoothness adjusts to the local properties of the signal. We address the problem of nonparametric regression and propose an (averaged) estimator obtained by using our nondecimated lifting technique teamed with empirical Bayes shrinkage. Simulations show that our proposed method has higher performance than competing techniques able to work on irregular data. Our construction also opens avenues for generating a ‘best’ representation, which we shall explore.     

On pseudo-values for regression analysis in competing risks models

For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15–27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their asymptotics (Klein and Andersen, Biometrics 61:223–229, 2005). The key is a second order von Mises expansion of the Aalen-Johansen estimator which yields an appropriate representation of the pseudo-values. The method is illustrated with data from a clinical study on total joint replacement. In the application we consider for comparison the estimates obtained with the Fine and Gray approach (J Am Stat Assoc 94:496–509, 1999) and also time-dependent solutions of pseudo-value regression equations.     

Approximate Bayesianity of Frequentist Confidence Intervals for a Binomial Proportion

The well-known Wilson and Agresti–Coull confidence intervals for a binomial proportion p are centered around a Bayesian estimator. Using this as a starting point, similarities between frequentist confidence intervals for proportions and Bayesian credible intervals based on low-informative priors are studied using asymptotic expansions. A Bayesian motivation for a large class of frequentist confidence intervals is provided. It is shown that the likelihood ratio interval for p approximates a Bayesian credible interval based on Kerman’s neutral noninformative conjugate prior up to O(n^{? 1}) in the confidence bounds. For the significance level α ? 0.317, the Bayesian interval based on the Jeffreys’ prior is then shown to be a compromise between the likelihood ratio and Wilson intervals. Supplementary materials for this article are available online.     

Improved likelihood inferences for Weibull regression model

A general procedure is developed for bias-correcting the maximum likelihood estimators (MLEs) of the parameters of Weibull regression model with either complete or right-censored data. Following the bias correction, variance corrections and hence improved t-ratios for model parameters are presented. Potentially improved t-ratios for other reliability-related quantities are also discussed. Simulation results show that the proposed method is effective in correcting the bias of the MLEs, and the resulted t-ratios generally improve over the regular t-ratios.     

Testing equality of generalized variances of k multivariate normal populations

Generalized variance is a measure of dispersion of multivariate data. Comparison of dispersion of multivariate data is one of the favorite issues for multivariate quality control, generalized homogeneity of multidimensional scatter, etc. In this article, the problem of testing equality of generalized variances of k multivariate normal populations by using the Bartlett's modified likelihood ratio test (BMLRT) is proposed. Simulations to compare the Type I error rate and power of the BMLRT and the likelihood ratio test (LRT) methods are performed. These simulations show that the BMLRT method has a better chi-square approximation under the null hypothesis. Finally, a practical example is given.     

Asymptotic expansions of density of normalized extremes from logarithmic general error distribution

Logarithmic general error distribution is an extension of the log-normal distribution. In this paper, the asymptotic expansions of densities of normalized maximum from logarithmic general error distribution are derived under two different kinds of normalized constants. By applying the main results, the higher-order expansions of moments of maxima are established.     

中外网络环境下著作权限制制度的比较及启示

网络技术的应用带来了著作权人权利范围的扩张,从而破坏了权利人与公众之间的利益平衡,激化了权利人与使用者的矛盾。目前,我国还没有关于网络环境下著作权权利限制方面的明确立法,而网络环境下著作权的纠纷却层出不穷,给司法实践中的具体操作带来了困难。通过对国外相关的立法经验和国际条约的规定进行分析和比较,可得出有益的启示,应从权能限制即合理使用和法定许可这两个方面来构建我国网络环境下著作权的权利限制。