Customizing Generalizations of the Kolmogorov-Smirnov Goodness-of-fit Test

This paper presents a method of customizing goodness-of-fit tests that transforms the empirical distribution function in such a way as to create tests for certain alternatives. Using the @ , g transform described in Blom(1958), one can create non-parametric tests for an assortment of alternative distributions. As examples, three new ( f , g )-corrected Kolmogorov-Smirnov tests for goodness-of-fit are discussed. One of these tests is powerful for testing whether or not the data come from an alternative that is heavier in the tails. Another test identifies whether or not the data come from an alternative which is heavier in the middle of the distribution. The last test identifies if the data come from an alternative in which the first or third quartile is far from the corresponding quartile of the hypothesized distribution. The behavior of the three new tests is investigated through a power study.     

Testing the equality of two independent regression models

In some situations, for example in agriculture, biology, hydrology, and psychology, researchers wish to determine whether the relationship between response variable and predictor variables differs in two populations. In other words, we are interested in comparing two regression models for two independent datasets. In this work, we will use the parametric and nonparametric methods to establish hypothesis testing for the equality of two independent regression models. Then the simulation study is provided to investigate the performance of the proposed method.     

Construction and Nonparametric Testing of Orthogonal Arrays through Algebraic Strata and Inequivalent Permutation Matrices

In this article we use a new methodology, based on algebraic strata, to generate the class of all the orthogonal arrays of given size and strength. From this class we extract all the non isomorphic orthogonal arrays. Then, using all these non isomorphic orthogonal arrays, we suggest a method based on the inequivalent matrices permutations testing procedures Basso et al. (2004 Basso , D. , Evangelaras , H. , Koukouvinos , C. , Salmaso , L. ( 2004 ). Nonparametric testing for main effects on inequivalent designs. Proc. 7th Int. Workshop Model-Oriented Design Anal. Heeze, Netherlands, June 14–18 . [Google Scholar]) in order to obtain separate permutation tests for the effects in unreplicated mixed level fractional factorial designs. In order to validate the proposed method we perform a Monte Carlo simulation study and find out that the permutation tests appear to be a valid solution for testing effects, in particular when the usual normality assumptions cannot be justified.     

Estimating the error distribution function in semiparametric additive regression models

We consider semiparametric additive regression models with a linear parametric part and a nonparametric part, both involving multivariate covariates. For the nonparametric part we assume two models. In the first, the regression function is unspecified and smooth; in the second, the regression function is additive with smooth components. Depending on the model, the regression curve is estimated by suitable least squares methods. The resulting residual-based empirical distribution function is shown to differ from the error-based empirical distribution function by an additive expression, up to a uniformly negligible remainder term. This result implies a functional central limit theorem for the residual-based empirical distribution function. It is used to test for normal errors.     

A new way of quantifying the symmetry of a random variable: Estimation and hypothesis testing

New measures of skewness for real-valued random variables are proposed. The measures are based on a functional representation of real-valued random variables. Specifically, the expected value of the transformed random variable can be used to characterize the distribution of the original variable. Firstly, estimators of the proposed skewness measures are analyzed. Secondly, asymptotic tests for symmetry are developed. The tests are consistent for both discrete and continuous distributions. Bootstrap versions improving the empirical results for moderated and small samples are provided. Some simulations illustrate the performance of the tests in comparison to other methods. The results show that our procedures are competitive and have some practical advantages.     

购买力平价及其在亚洲新兴市场中的实证分析

 作为最重要的汇率决定理论之一,购买力平价被广泛应用于实证研究,但是重点针对亚洲新兴市场的研究依然有限。本文对七个亚洲新兴市场进行了购买力平价理论长期均衡关系的实证检验分析。针对购买力平价理论,作者运用单位根检验和协整检验进行数据分析。数据采用1957年至2011年的汇率（以美元作为基础汇率）及季度价格水平（本文采用CPI作为价格水平指数）。实证检验结果表明购买力平价理论的长期均衡在亚洲新兴市场中均不成立。文章最后提出了一些或许会导致其不理想结论的因素,并针对文章的实证研究得出新的改进方法。     

无领导小组讨论的评分者效应分析

以大学生为研究对象,实施无领导小组讨论测评,探讨培训组与非培训组评分者的信效度差异。通过相关分析、验证性因素分析等方法检验评分者的内部一致性、评分者间信度、组间与组内差异、结构效度及效标关联效度。结果显示,培训效应对评分者影响显著,经培训与未经培训的评分者组间差异显著,培训组评分结果的效标关联效度优于非培训组。对评分者进行系统的培训能有效促进客观公正地实施测评,提高测评结果准确性。     

中日总产出波动与服务产业结构演变互动关系比较分析

通过中国和日本2000-2011年的实际经济数据,采用HP滤波方法获取周期数据,对中日总产出波动与服务产业结构演变关系进行实证分析发现：第一,分类服务产业结构演变显示,中日两国传统服务业比重呈不断下降趋势,相比传统服务业,两国现代服务业比重呈不断上升趋势;第二,周期波动和相关性检验显示,中国服务产业与总产出周期波动显著高于日本,中国现代服务业和社会服务业的失衡性发展,极有可能对传统服务业产生负效应;第三,格兰杰短期因果关系检验显示,中日服务产业和产出总量指标分别在1996-2011和1986-2011年期间存在显著的双向格兰杰因果关系,尤其“金融保险业”和“房地产、租赁与商务业”是总产出的单向格兰杰原因,因此应对中国过热的房地产服务业给予更多关注,避免在中国重现“日本失去的十年”.     

PSC中“命题说话”项失分的原因及解决方法

通过对普通话水平测试过程中学生完成各项测试内容得分情况进行分析,发现最后一项"命题说话"失分率普遍较高。导致"命题说话"项失分多的原因,可以归纳为语音性失误和非语音性失误。语音性失误中如果是超音质的失误,根据定量分析进行定性降档处理。     

国际航运发展综合试验区先行先试政策

从分析国际航运发展综合试验区先行先试的内涵机制出发,研究其发展战略定位;从政府航运监管政策、航运税制改革以及航运高端服务培育等几个方面研究其先行先试的政策体系,并结合国际经验,具体分析了相关航运政策.