A computational investigation of conover's kolmogorov-smirnov test for discrete distributions

The tabled significance values of the Kolmogorov-Smirnov goodness-of-fit statistic determined for continuous underlying distributions are conservative for applications involving discrete underlying distributions. Conover (1972) proposed an efficient method for computing the exact significance level of the Kolmogorov-Smirnov test for discrete distributions; however, he warned against its use for large sample sizes because “the calculations become too difficult.”

In this work we explore the relationship between sample size and the computational effectiveness of Conover's formulas, where “computational effectiveness” is taken to mean the accuracy attained with a fixed precision of machine arithmetic. The nature of the difficulties in calculations is pointed out. It is indicated that, despite these difficulties, Conover's method of computing the Kolmogorov-Smirnov significance level for discrete distributions can still be a useful tool for a wide range of sample sizes.     

Comparison of permutation methods for the partial correlation and partial mantel tests

This study compares empirical type I error and power of different permutation techniques that can be used for partial correlation analysis involving three data vectors and for partial Mantel tests. The partial Mantel test is a form of first-order partial correlation analysis involving three distance matrices which is widely used in such fields as population genetics, ecology, anthropology, psychometry and sociology. The methods compared are the following: (1) permute the objects in one of the vectors (or matrices); (2) permute the residuals of a null model; (3) correlate residualized vector 1 (or matrix A) to residualized vector 2 (or matrix B); permute one of the residualized vectors (or matrices); (4) permute the residuals of a full model. In the partial correlation study, the results were compared to those of the parametric t-test which provides a reference under normality. Simulations were carried out to measure the type I error and power of these permutatio methods, using normal and non-normal data, without and with an outlier. There were 10 000 simulations for each situation (100 000 when n = 5); 999 permutations were produced per test where permutations were used. The recommended testing procedures are the following:(a) In partial correlation analysis, most methods can be used most of the time. The parametric t-test should not be used with highly skewed data. Permutation of the raw data should be avoided only when highly skewed data are combined with outliers in the covariable. Methods implying permutation of residuals, which are known to only have asymptotically exact significance levels, should not be used when highly skewed data are combined with small sample size. (b) In partial Mantel tests, method 2 can always be used, except when highly skewed data are combined with small sample size. (c) With small sample sizes, one should carefully examine the data before partial correlation or partial Mantel analysis. For highly skewed data, permutation of the raw data has correct type I error in the absence of outliers. When highly skewed data are combined with outliers in the covariable vector or matrix, it is still recommended to use the permutation of raw data. (d) Method 3 should never be used.     

Saddlepoint approximations for some models of circular data

In this article we provide saddlepoint approximations for some important models of circular data. The particularity of these saddlepoint approximations is that they do not require solving the saddlepoint equation iteratively, so their evaluation is immediate. We first give very accurate approximations to P-values, critical values and power functions for some optimal tests regarding the concentration parameter under wrapped symmetric α-stable and circular normal models. Then, we consider an approximation to the distribution of a projection of the two-dimensional Pearson random walk with exponential step sizes.     

要素所有者的谈判力与企业权益分配格局

在全面解释“谈判力”涵义的基础上,着重论证了谈判力与企业权益分配格局的关系,并据此提出了改进我国企业权益分配状况的建议。     

第二大股东持股的治理效应——基于上市公司的实证分析

本文以763家上市公司2003年的横截面数据为样本,通过考察公司绩效与第二大股东持股之间的经验关系,考察了第二大股东持股的治理功能。通过结合上市公司数据建立一个多元模型,来说明第二大股东是如何监督第一大股东,影响公司价值的。研究发现,我国并不存在有效的股权制衡机制,第二大股东的存在没有显示出积极的治理激励功能,没有反映出第二大股东对第一大股东的监督激励作用。在我国目前的制度背景下,相对控股是一种最佳的平衡状态。     

村民自治：农村基层权力合法性基础的合理调整

任何政治权力系统都必须建立在权力合法性基础之上 ,方可得以稳定和巩固。我国国家行政权力合法性的本质是权力来源于对人民利益的实现能力和程度。我国农村基层权力合法性基础经历了稳定、危机显现、合理调整的发展历程。     

日元对美元汇率的变化及其原因分析

自实行浮动汇率制到20世纪90年代上半期,日元持续升值,成为主要的世界货币之一。决定这一长期走势的基本原因是日元对美元购买力平价的提高。而经济实力的消长则是购买力平价提高的物质基础。20世纪90年代以来,日元对美元的购买力平价趋于稳定,从而结束了日元长期升值的趋势。在上述过程中,国家的宏观经济政策、国际间利率差别、跨国资本流动以及一些突发事件的影响成为汇率在短期内波动的直接原因。     

空间不均匀的Boltzmann方程的稳定性

摘要：Boltzmann方程是描述稀薄气体变化规律的重要微分方程之一,如果方程的初始状态是真空附近的一个扰动,并且在无穷远处以幂指数形式快速收敛到零,同时分析了空间不均匀的Boltzmann方程的稳定性。为了得到该方程的稳定性,首先引入了几个非线性泛函并时它们作适当的估计,然后利用Gronwall不等式证明空间不均匀的Bohzmann方程的稳定性。     

论中国共产党政权主张的演变

第一次大革命失败后 ,中国共产党对在中国建立什么样的政权作了有益的探索。中国共产党根据各个时期革命的中心任务和阶级关系的变化 ,相继提出了建立民权主义代表制度革命政权、苏维埃模式政权、国防政府政权、人民共和国政权、民主共和国政权等主张和设想 ,最终提出了建立适合中国国情的人民民主政权的主张