Inferences on the coefficient of variation of an inverse gaussian distribution

The likelihood ratio test for a characteristic parameter of the inverse Gaussian distribution is derived. The parameter of interest characterizes the coefficient of variation, the skewness and the kurtosis of the distribution. The distribution of the test statistic is presented in a simplified form. Useful quanfiles of the distribution are given. Methods for constructing confidence bounds for the parameter, including Bayes highest posterior density intervals, are considered.     

A NONPARAMETRIC TEST OF SYMMETRY VERSUS ASYMMETRY FOR RANKED-SET SAMPLES

This paper introduces a nonparametric test of symmetry for ranked-set samples to test the asymmetry of the underlying distribution. The test statistic is constructed from the Cramér-von Mises distance function which measures the distance between two probability models. The null distribution of the test statistic is established by constructing symmetric bootstrap samples from a given ranked-set sample. It is shown that the type I error probabilities are stable across all practical symmetric distributions and the test has high power for asymmetric distributions.     

Generalized Least Squares Estimation in Contingency Tables Analysis: Asymptotic Properties and Applications

Different sorts of bilinear models (models with bilinear interaction terms) are currently used when analyzing contingency tables: association models, correlation models... All these can be included in a general family of bilinear models: power models. In this framework, Maximum Likelihood (ML) estimation is not always possible, as explained in an introductory example. Thus, Generalized Least Squares (GLS) estimation is sometimes needed in order to estimate parameters. A subclass of power models is then considered in this paper: separable reduced-rank (SRR) models. They allow an optimal choice of weights for GLS estimation and simplifications in asymptotic studies concerning GLS estimators. Power 2 models belong to the subclass of SRR models and the asymptotic properties of GLS estimators are established. Similar results are also established for association models which are not SRR models. However, these results are more difficult to prove. Finally, 2 examples are considered to illustrate our results.     

H_3 SiF的谐振力场和振转光谱常数的从头算研究

用B3LYP、B3PW91和MP2方法在6-311G(2df,2pd),6-311G(3df,3pd),cc-pVQZ基组水平上对H3SiF的谐振力场和振转光谱进行了研究.将计算得到的平衡几何结构(包括键长、键角)、转动常数、谐振频率和四次离心畸变常数分别与已有的实验值和理论值进行比较.由密度泛函方法计算得到的数据是可信的.     

《九歌》“东皇太一”祭祀渊源考论

＂东皇太一＂的神格与太一祭祀的渊源,是《楚辞》研究中争议较大的问题。文章从道家哲学与方术对楚国祭祀礼仪之影响的角度,结合考古发现,对以上问题加以探析,认为＂太一＂是创世神、祖先神与观念神的统一,根植于楚国的神话土壤,又孳乳于道家关于世界本原的哲学,经过战国中晚期道家、方士的鼓吹,才从哲学范畴演变为方士崇拜的至上神,最终进入楚王室的郊祀大典。     

基于DSR模型的淮河流域生态安全评价研究

淮河流域六安段饮用水源污染隐患突出,生态功能下降,季节性污染严重,城区水域景观功能弱化。基于DSR模型,根据研究区域的实际情况,选取淮河流域(六安段)的生态安全评价指标,建立生态安全评价模型,对2005年至2010年淮河流域六安段的生态安全变化进行研究。结果表明:2005年至2010年,淮河流域六安段生态安全状况正在不断改善,生态安全建设取得了阶段性的成果,但是生态安全建设的任务依然艰巨,其仍然是社会发展和经济建设中的重要战略,人类不仅要合理地利用自然资源,同时也要采取措施,减轻和解除生态环境的威胁,从而使生态系统能够保持健康和完整。     

Analyzing clustered count data with a cluster-specific random effect zero-inflated Conway–Maxwell–Poisson distribution

Count data analysis techniques have been developed in biological and medical research areas. In particular, zero-inflated versions of parametric count distributions have been used to model excessive zeros that are often present in these assays. The most common count distributions for analyzing such data are Poisson and negative binomial. However, a Poisson distribution can only handle equidispersed data and a negative binomial distribution can only cope with overdispersion. However, a Conway–Maxwell–Poisson (CMP) distribution [4] can handle a wide range of dispersion. We show, with an illustrative data set on next-generation sequencing of maize hybrids, that both underdispersion and overdispersion can be present in genomic data. Furthermore, the maize data set consists of clustered observations and, therefore, we develop inference procedures for a zero-inflated CMP regression that incorporates a cluster-specific random effect term. Unlike the Gaussian models, the underlying likelihood is computationally challenging. We use a numerical approximation via a Gaussian quadrature to circumvent this issue. A test for checking zero-inflation has also been developed in our setting. Finite sample properties of our estimators and test have been investigated by extensive simulations. Finally, the statistical methodology has been applied to analyze the maize data mentioned before.     

Hausman-type tests for individual and time effects in the panel regression model with incomplete data

By comparing estimators of the variance of idiosyncratic error at different robust levels, two Hausman-type test statistics are respectively constructed for the existence of individual and time effects in the panel regression model with incomplete data. The resultant test statistics have several desired properties. Firstly, they are robust to the presence of one effect when the other is tested. Secondly, they are immune to the non-normal distribution of the disturbances since the distributional conditions are not needed in the construction of the statistics. Thirdly, they have more robust performances than the main competitors in the literature when the covariates are correlated with the effects. Additionally, they are very simple and have no heavy computational burden. Joint tests for both of the two effects are also discussed. Monte Carlo evidence shows that the proposed tests have desired finite sample properties, and a real data analysis gives further support.     

The effect of teaching strategies on student achievement: An analysis using TALIS-PISA-link

The present study investigates the effects of different teaching strategies on student achievement using data from the so-called TALIS-PISA link created by the OECD. This is a recently developed instrument that allows for connecting data about teacher characteristics and practices collected in the TALIS (Teaching and Learning International Survey) survey with students’ academic performance measured in PISA (Programme for International Student Assessment). Our empirical strategy is based on an instrumental variable (IV) approach. Our results suggest that traditional teaching methods have a positive influence on students’ proficiency in mathematics, while the implementation of more innovative active learning strategies seem to have a negative impact on student achievement.