A Geometric Examination of Linear Model Assumptions

From a geometric perspective, linear model theory relies on a single assumption, that (‘corrected’) data vector directions are uniformly distributed in Euclidean space. We use this perspective to explore pictorially the effects of violations of the traditional assumptions (normality, independence and homogeneity of variance) on the Type I error rate. First, for several non‐normal distributions we draw geometric pictures and carry out simulations to show how the effects of non‐normality diminish with increased parent distribution symmetry and continuity, and increased sample size. Second, we explore the effects of dependencies on Type I error rate. Third, we use simulation and geometry to investigate the effect of heterogeneity of variance on Type I error rate. We conclude, in a fresh way, that independence and homogeneity of variance are more important assumptions than normality. The practical implication is that statisticians and authors of statistical computing packages need to pay more attention to the correctness of these assumptions than to normality.     

Facilitating the Calculation of the Efficient Score Using Symbolic Computing

The score statistic continues to be a fundamental tool for statistical inference. In the analysis of data from high-throughput genomic assays, inference on the basis of the score usually enjoys greater stability, considerably higher computational efficiency, and lends itself more readily to the use of resampling methods than the asymptotically equivalent Wald or likelihood ratio tests. The score function often depends on a set of unknown nuisance parameters which have to be replaced by estimators, but can be improved by calculating the efficient score, which accounts for the variability induced by estimating these parameters. Manual derivation of the efficient score is tedious and error-prone, so we illustrate using computer algebra to facilitate this derivation. We demonstrate this process within the context of a standard example from genetic association analyses, though the techniques shown here could be applied to any derivation, and have a place in the toolbox of any modern statistician. We further show how the resulting symbolic expressions can be readily ported to compiled languages, to develop fast numerical algorithms for high-throughput genomic analysis. We conclude by considering extensions of this approach. The code featured in this report is available online as part of the supplementary material.     

Symbolic Itô calculus in AXIOM: An ongoing story

Symbolic Itô calculus refers both to the implementation of Itô calculus in a computer algebra package and to its application. This article reports on progress in the implementation of Itô calculus in the powerful and innovative computer algebra package AXIOM, in the context of a decade of previous implementations and applications. It is shown how the elegant algebraic structure underlying the expressive and effective formalism of Itô calculus can be implemented directly in AXIOM using the package's programmable facilities for strong typing of computational objects. An application is given of the use of the implementation to provide calculations for a new proof, based on stochastic differentials, of the Mardia-Dryden distribution from statistical shape theory.     

SU(2)和SU(1,1)在相空间中指数算符的正规乘积和反正规乘积的简单实现

通过指数算符的分解,给出了SU(2)和SU(1,1)在相空间中指数算符的正规和反正规乘积形式.     

SnD_4分子振动谱的代数模型计算

利用U(2 )代数模型 ,对1 2 0 SnD4 分子的高激发伸缩振动能谱进行了理论计算 (1≤V≤6 ,V为1 2 0 SnD4 分子的总振动量子数 ) ,计算结果与最新观测到的能谱数据符合得很好 ,其标准偏差为 0 .1 2 4cm-1 .     

Embedding time in positions: Temporal measures of centrality for social network analysis

Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra, we propose three temporal equivalents to positional network measures that incorporate time and sequence. We demonstrate how these temporal equivalents can be applied to an empirical context and compare the results with their static counterparts. We show that, compared to their temporal counterparts, static measures applied to interaction networks obscure meaningful differences in the way in which individuals accumulate alters over time, conceal potential disconnections in the network by overestimating reachability, and bias the distribution of betweenness centrality, which can affect the identification of key individuals in the network.     

Scalar Statistics Which Have Constant Regression on the Mean of a Riesz Distribution

We propose a new estimator for the population variance using an auxiliary variable in simple random sampling and obtain the equations for its mean square error (MSE) and bias. In addition, theoretically, we show that the proposed estimator is more efficient than the traditional ratio and regression estimators, suggested by Isaki (1983 Isaki , C. T. (1983). Variance estimation using auxiliary information. J. Amer. Statist. Assoc. 78:117–123.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]), under certain conditions that are defined in this article. These conditions are satisfied with a numerical example.     

浅谈图论与线性代数的联系

图论是数学的一个重要分支,它的应用也十分广泛,与此同时它与其他的数学分支也有着重要的联系,本文主要讨论图论与线性代数的联系,我们将运用线性代数中的内容解决图论中的问题。     

C_∞的旋量表示

给出了完备无限秩仿射李代数Ａ∞的水平为１的不可约旋量表示，并在Ａ∞的不可约表示的基础上给出了Ｃ∞的一类基本模