浅论政府自利性扩张及其控制途径

政府的自利性具有扩张性特征,如果不加以遏制,可能导致＂权力寻租＂行为的盛行,削弱政府的执行力,影响公共政策的公正性,并造成部门利益法制化和群体腐败的严重后果。因此,只有通过构建有限政府,严格控制政府自由裁量权,建立和完善引咎辞职制度,坚持行政权力运行公开透明,加强体制外监督,降低行政消费水平等途径,才能有效地遏制政府自利性的恶性膨胀。     

A general procedure for deriving distributions

A general procedure for deriving the exact and asymptotic distributions of a certain class of test statistics in multivariate analysis is proposed. The method is based on an asymptotic expansion of gamma ratios in terms of generalized Bernoulli polynomials. The exact and asymptotic results are obtained and the method is illustrated in the problem of testing linear hypotheses in the multinomial case. In this problem the method yields Box's (1949) expansion as a special case.     

西方文明纵览与反思：《画里画外》研究

海勒出版于1988年的《画里画外》是一部内容丰富的历史小说。本文择要讨论了三个方面：其一是重新审视公元前5世纪雅典黄金时代,揭示战争的非理性和盲目性,以及战争与政治、经济、道德之间错综复杂的关系;其二是选取近代荷兰这个特定历史时期,凸显欧洲资本主义萌芽时期的经济、垄断和扩张及资本主义的本质;其三是通过展示若干历史名人的人生哲学和人生体验,表现作家对于不同的人生信念和不同的人类行为的深远遐想。     

Exponentiated models preserve stochastic orderings of parallel and series systems

Abstract

In this paper, we establish that the usual stochastic, hazard rate, reversed hazard rate, likelihood ratio, dispersive and star orders are all preserved for parallel systems under exponentiated models for lifetimes of components. We then use the multiple-outlier exponentiated gamma models to illustrate this result. Finally, we consider the dual family with exponentiated survival function and establish similar results for series systems. The results established here extend some well-known results for series and parallel systems arising from different exponentiated distributions such as generalized exponential and exponentiated Weibull, established previously in the literature.     

Functional Autoregression for Sparsely Sampled Data

We develop a hierarchical Gaussian process model for forecasting and inference of functional time series data. Unlike existing methods, our approach is especially suited for sparsely or irregularly sampled curves and for curves sampled with nonnegligible measurement error. The latent process is dynamically modeled as a functional autoregression (FAR) with Gaussian process innovations. We propose a fully nonparametric dynamic functional factor model for the dynamic innovation process, with broader applicability and improved computational efficiency over standard Gaussian process models. We prove finite-sample forecasting and interpolation optimality properties of the proposed model, which remain valid with the Gaussian assumption relaxed. An efficient Gibbs sampling algorithm is developed for estimation, inference, and forecasting, with extensions for FAR(p) models with model averaging over the lag p. Extensive simulations demonstrate substantial improvements in forecasting performance and recovery of the autoregressive surface over competing methods, especially under sparse designs. We apply the proposed methods to forecast nominal and real yield curves using daily U.S. data. Real yields are observed more sparsely than nominal yields, yet the proposed methods are highly competitive in both settings. Supplementary materials, including R code and the yield curve data, are available online.     

会计稳健性抑制卖空了吗?——基于企业风险和会计稳健性时序特征的分析

会计稳健性会及时披露企业负面消息,这种特性会抑制股价高估,减少融券卖空行为。以我国2010—2016年A股市场所有融资融券标的公司为样本,分析了公司会计稳健性水平对融券卖空程度的影响。研究发现,会计稳健性水平的提升能够显著抑制市场卖空行为,且公司经营风险越大,这种抑制作用越明显。进而,考虑公司会计稳健性长期历史水平,即会计稳健性时间序列特征对稳健性与卖空水平之间关系的影响。实证结果显示,"持续稳健"与"持续不稳健"分别加强和减弱了会计稳健性对卖空的抑制作用,而"非持续稳健"则未表现出明显的影响。研究结论说明公司增加会计稳健性能抑制市场卖空行为,尤其对于经营风险高的企业更是如此,而且企业应保持长时间持续稳健地披露会计信息,以此稳定投资者的稳健性预期,才能有效地发挥会计稳健性对卖空的抑制作用。     

Sequential shrinkage estimation of independent normal means with unkown variances

The Paper considers estimation of the p(> 3)-variate normal mean when the variance-covariance matrix is diagonal with unknown diagonal elements. A class of James-Stein estimators is developed, and is compared with the sample mean under an empirical minimax stopping rule. Asymptotic risk expansions are provided for both the sequential sample mean and the sequential James-Stein estimators. It is shown that the James-Stein estimators dominate the sample mean in a certain asymptotic sense.     

逻辑函数XOS展开式和COD展开式的转换

在逻辑函数的XOS展开式和COD展开式的基础上,详细讨论了逻辑函数ej系数和gj系数间的关系, 并提出了两者的矩阵转换法,举例说明了转换过程.该方法揭示了ej系数和系数gj的内在联系,具有较好的实用性.     

高校英语专业语言学系列课程内容整合研究

本文论述在自主学习理论和建构主义理论的指导下进行高校英语专业语言学系列课程内容整合。     

Efficient Regularization Parameter Selection Via Information Criteria

In a nonlinear regression model based on a regularization method, selection of appropriate regularization parameters is crucial. Information criteria such as generalized information criterion (GIC) and generalized Bayesian information criterion (GBIC) are useful for selecting the optimal regularization parameters. However, the optimal parameter is often determined by calculating information criterion for all candidate regularization parameters, and so the computational cost is high. One simple method by which to accomplish this is to regard GIC or GBIC as a function of the regularization parameters and to find a value minimizing GIC or GBIC. However, it is unclear how to solve the optimization problem. In the present article, we propose an efficient Newton–Raphson type iterative method for selecting optimal regularization parameters with respect to GIC or GBIC in a nonlinear regression model based on basis expansions. This method reduces the computational time remarkably compared to the grid search and can select more suitable regularization parameters. The effectiveness of the method is illustrated through real data examples.