Five Ways of Reducing the Crank–Nicolson Oscillations

Crank—Nicolson is a popular method for solving parabolic equations because it is unconditionally stable and second-order accurate. One drawback of CN is that it responds to jump discontinuities in the initial conditions with oscillations which are weakly damped and therefore may persist for a long time. We compare a selection of methods to reduce the amplitude of these oscillations.This revised version was published online in October 2005 with corrections to the Cover Date.     

On Linear Combinations of Multivariate Generalized Sampling Type Series

In this paper suitable linear combinations for a multivariate extension of the generalized sampling series are considered, also in the Kantorovich version. These combinations provide a better order of approximation. Finally the particular example of the Bochner-Riesz kernel is discussed.     

Sampling Schemes for Bayesian Variable Selection in Generalized Linear Models

Bayesian approaches to prediction and the assessment of predictive uncertainty in generalized linear models are often based on averaging predictions over different models, and this requires methods for accounting for model uncertainty. When there are linear dependencies among potential predictor variables in a generalized linear model, existing Markov chain Monte Carlo algorithms for sampling from the posterior distribution on the model and parameter space in Bayesian variable selection problems may not work well. This article describes a sampling algorithm based on the Swendsen-Wang algorithm for the Ising model, and which works well when the predictors are far from orthogonality. In problems of variable selection for generalized linear models we can index different models by a binary parameter vector, where each binary variable indicates whether or not a given predictor variable is included in the model. The posterior distribution on the model is a distribution on this collection of binary strings, and by thinking of this posterior distribution as a binary spatial field we apply a sampling scheme inspired by the Swendsen-Wang algorithm for the Ising model in order to sample from the model posterior distribution. The algorithm we describe extends a similar algorithm for variable selection problems in linear models. The benefits of the algorithm are demonstrated for both real and simulated data.     

Generalized Embedding Schemes

Covering projections are used to provide a logical foundation for the generalized embedding schemes which describe embeddings of graphs on closed surfaces that are not necessarily orientable. Criteria are provided to resolve the question of when such schemes describe the same embedding, and when that embedding is orientable. The schemes are then applied to derive some interpolation-type theorems for embeddings on closed surfaces.     

Linear Key Predistribution Schemes

In a key predistribution scheme, some secret information is distributed among a set of users. For a given family of privileged groups, this secret information must enable every user in a privileged group to compute a common key associated with that group. Besides, this common key must remain unknown to some specified coalitions of users outside the privileged group. We present in this paper a new model, based on linear algebraic techniques, for the design of key predistribution schemes that unifies all previous proposals. This new model provides a common mathematical formulation and a better understanding of key predistribution schemes. Two new families of key predistribution schemes that are obtained by using this model are presented. Those families provide, for some specification structures, schemes that have better information rates than the ones given in previous proposals or fit in situations that have not been considered before.     

广义线性模型(四)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分 3部分 ;建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L .Fahrmeir等人的《MultivariateStatisticalModelingBasedonGeneralizedLinearModels》。     

广义线性模型(七)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分3部分:建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L.Fahrmeir等人的《MultivariateStatisticalModelingBasedonGeneralizedLinearModels》。     

广义线性模型(九)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分3部分:建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L.Fahrmeir等人的《MultivariateStatisticalMod elingBasedonGeneralizedLinearModels》。     

广义线性模型(五)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分 3部分 :建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L .Fahrmeir等人的《MultivariateStatisticalModelingBasedonGeneralizedLinearModels》。     

广义线性模型(六)

本讲座是广义线性模型这个题目的一个比较系统的介绍。主要分 3部分 :建模、统计分析与模型选择和诊断。写作时依据的主要参考资料是L .Fahrmeir等人的 :《MultivariateStatisticalModel ingBasedonGeneralizedLinearModles》。     

Fredholmness of Linear Combinations of Two Idempotents

Let E and F be idempotent operators on a complex Hilbert space, and let a and b be nonzero scalars with a + b ≠ 0. We prove that aE + bF is Fredholm if and only if E + F is, thus answering affirmatively a question asked by Koliha and Rakočević.      

反幂等阵线性组合的反幂等性

讨论了反幂等阵线性组合的幂等性,指出可对角化矩阵可表示为反幂等阵的线性组合,并由此得到了由非奇异矩阵构造两两正交且可交换的反幂等阵的一种方法.     

m次数量幂等矩阵线性组合的可逆性

如果有非零数λ与μ使Pm=λP,Qm=μQ,则称P,Q分别是由λ,μ确定的m次数量幂等矩阵．本文证明了,若有非零数a与b,当μam-1（-1）m-1μbm-1≠0时,使可交换的分别由λ,μ确定的m次数量幂等矩阵P,Q的线性组合aP＋bQ是可逆的,那么对任意非零数u,u,当λμm-1-（-1）m-1μvm-1≠0时,uP＋vQ也是可逆的．本文主要结果和方法的应用,可以推广已有文献的2次、3次幂等矩阵的线性组合可逆的结论．     

Merging of Linear Combinations to Semistable Laws

We prove merge theorems along the entire sequence of natural numbers for the distribution functions of suitably centered and normed linear combinations of independent and identically distributed random variables from the domain of geometric partial attraction of any non-normal semistable law. Surprisingly, for some sequences of linear combinations, not too far from those with equal weights, the merge theorems reduce to ordinary asymptotic distributions with semistable limits. The proofs require working out general conditions for merging in terms of characteristic functions.     

Linear Generalized Analytic Functions

Complex-valued continuous functions are approximated using solutions of complex partial differential equations of Vekua type.     

Bernstein-Type Inequalities for Linear Combinations of Shifted Gaussians

Let P_n be the collection of all polynomials of degree at mostn with real coefficients. A subtle Bernstein-type extremal problemis solved by establishing the inequality for all , and m= 1, 2, ..., where c is an absolute constant and Some related inequalities and direct and inversetheorems about the approximation by elements of in L_q (R) are also discussed. 2000 Mathematics SubjectClassification 41A17 (primary).     

Baskakov算子线性组合的点态估计

本文利用Ditizian-Totik模给出Baskakov算子线性组合点态和整体逼近正逆定理的统一形式,得到了较高的逼近阶,并且刻画了该线性组合算子的逼近特征。     

Pointwise Estimates for Linear Combinations of Gamma Operators

For linear combinations of Gamma operators G_n,r(f,x), we give an equivalent theorem with (f,t), where (f,t) are the Ditzian-Totik moduli of smoothness ( ).AMS Subject Classification (1991): 41A25, 41A36.Supported by NSF of Hebei ProvinceSupported by NSF of Hebei Province     

A Linear Construction of Secret Sharing Schemes

In this paper, we will generalize the vector space construction due to Brickell. This generalization, introduced by Bertilsson, leads to secret sharing schemes with rational information rates in which the secret can be computed efficiently by each qualified group. A one to one correspondence between the generalized construction and linear block codes is stated, and a matrix characterization of the generalized construction is presented. It turns out that the approach of minimal codewords by Massey is a special case of this construction. For general access structures we present an outline of an algorithm for determining whether a rational number can be realized as information rate by means of the generalized vector space construction. If so, the algorithm produces a secret sharing scheme with this information rate.     

Pointwise Estimate for Linear Combinations of Bernstein-Kantorovich Operators

For linear combinations of Bernstein-Kantorovich operators K_n, r(f, x), we give an equivalent theorem with ω^2r_?^λ(f, t). The theorem unites the corresponding results of classical and Ditzian-Totik moduli of smoothness.