On 3-Steiner simplicial orderings

Let G be a connected graph and S a nonempty set of vertices of G. A Steiner tree for S is a connected subgraph of G containing S that has a minimum number of edges. The Steiner interval for S is the collection of all vertices in G that belong to some Steiner tree for S. Let k≥2 be an integer. A set X of vertices of G is k-Steiner convex if it contains the Steiner interval of every set of k vertices in X. A vertex x∈X is an extreme vertex of X if X?{x} is also k-Steiner convex. We call such vertices k-Steiner simplicial vertices. We characterize vertices that are 3-Steiner simplicial and give characterizations of two classes of graphs, namely the class of graphs for which every ordering produced by Lexicographic Breadth First Search is a 3-Steiner simplicial ordering and the class for which every ordering of every induced subgraph produced by Maximum Cardinality Search is a 3-Steiner simplicial ordering.     

A parameterized approach to modeling and forecasting mortality

A new method is proposed of constructing mortality forecasts. This parameterized approach utilizes Generalized Linear Models (GLMs), based on heteroscedastic Poisson (non-additive) error structures, and using an orthonormal polynomial design matrix. Principal Component (PC) analysis is then applied to the cross-sectional fitted parameters. The produced model can be viewed either as a one-factor parameterized model where the time series are the fitted parameters, or as a principal component model, namely a log-bilinear hierarchical statistical association model of Goodman [Goodman, L.A., 1991. Measures, models, and graphical displays in the analysis of cross-classified data. J. Amer. Statist. Assoc. 86(416), 1085-1111] or equivalently as a generalized Lee-Carter model with p interaction terms. Mortality forecasts are obtained by applying dynamic linear regression models to the PCs. Two applications are presented: Sweden (1751-2006) and Greece (1957-2006).     

The uncertainties about the relationships risk–return–volatility in the Spanish stock market

The relationships between the market risk premium, its conditional variance and the risk-free rate in the Spanish stock market are studied in this paper. Using daily data, the above mentioned relations are analyzed by quasi maximum likelihood for an EGARCH-M(1,1) model with normal innovations and by nonparametric maximum likelihood for a semiparametric EGARCH-M(1,1) model with arbitrarily distributed innovations. It is worth mentioning that the conclusions differ from one model to the other.     

随机设计非线性混合模型的统计分析

本文研究了个体观察次数为随机的非线性 混合效应模型中参数的点估计以及区间估计. 在仅给出适当的矩条件下, 给出了固定效应、随机效应的方差阵以及误差方差的矩估计, 并证明了估计量的相合性及渐近正态性. 为给出误差方差以及随机效应方差分量的置信区间, 本文也给出了误差及随机效应的四阶矩估计. 随机模拟说明了方法的有效性.     

Semi-empirical likelihood confidence intervals for the differences of quantiles with missing data

Detecting population （group） differences is useful in many applications, such as medical research. In this paper, we explore the probabilistic theory for identifying the quantile differences .between two populations. Suppose that there are two populations x and y with missing data on both of them, where x is nonparametric and y is parametric. We are interested in constructing confidence intervals on the quantile differences of x and y. Random hot deck imputation is used to fill in missing data. Semi-empirical likelihood confidence intervals on the differences are constructed.     

Sums of nine almost equal prime cubes

We prove that each sufficiently large odd integer N can be written as sum of the form N = p1^3 ＋p2^3 ＋... ＋p9^3 with [pj - （N/9）^1/31 ≤ N^（1/3）-θ, where pj, j = 1,2,...,9, are primes and θ = （1/51） -ε.     

Maximum confidence measurements via probabilistic quantum cloning

Probabilistic quantum cloning(PQC) cannot copy a set of linearly dependent quantum states.In this paper,we show that if incorrect copies are allowed to be produced,linearly dependent quantum states may also be cloned by the PQC.By exploiting this kind of PQC to clone a special set of three linearly dependent quantum states,we derive the upper bound of the maximum confidence measure of a set.An explicit transformation of the maximum confidence measure is presented.     

氟苯类化合物19F NMR化学位移的计算

提出了计算氟苯类化合物¹⁹F NMR化学位移的公式：δ_cal（¹⁹F）=-113.5+Δo+Δm+Δp+C, 结合最小二乘法通过线性回归得到了20种取代基参数, 计算结果以160种氟苯类化合物的263个¹⁹F NMR化学位移数据为样本点作回归检验,置信度为99.5%,计算值与实验值的平均偏差为0.628,计算值与实验值的标准偏差为4.720,约有93.2%的¹⁹F NMR化学位移计算值的计算误差<7.0（相对误差<0.7%）.     

利用四段式测试题诊断高一学生化学键迷思概念

使用改编自迈阿密大学牛津分校Stacey Lowery Bretz的"化学键概念表征量表",并通过加设信心指数将其扩充为四段式测试题。利用本测试工具对浙江省2所普通高中共260名学生进行测试。结果显示,被试存在"高信心指数错解"和"低信心指数正解"的情况,并探查出7个典型的化学键迷思概念,其中4个为呈现出较高信心指数的真性迷思概念。信心指数在一定程度上弥补了二段式工具的缺陷。     

基于广义极值的混沌电场峰值分布研究

通过分析峰值分布及广义极值分布理论关于混沌电场峰值分布的特点,获得一种混沌电场峰值分布的计算方法,结合Bootstrap重采样技术,提出了混沌电场峰值分布参数估计方法,该方法吸取了重采样技术估计的优点,对分布参数置信区间的估计更为准确、实用。以蒙特卡罗仿真和某机械搅拌混响室内电场数据为实例,结果表明,与传统的正态近似法、百分位法、BC-t等方法相比,其计算结果与实际结果更为吻合,证明了该方法具有更高的准确度。