美、加公共管理领域非学位教育的借鉴意义

本文就美、加高校在公共管理领域从业人员非学位教育方面的特色从培训计划、方法、师资和评估四个方面进行分析, 对其借鉴意义进行了探讨。     

变换法在解微分方程中的应用

变量代换法是解常微分方程的一种辅助方法，它能使问题简化．本文通过联系实例给出了变换在求解微分方程中的具体应用。     

建国50多年来中国外交的基本特征论析

建国50多年来,中国共产党三代领导集体在中国外交政策和策略等方面,表现了相当的一致性。在这些方面,后一代领导集体与前一代领导集体之间有着承继关系。当然,后一代领导集体也有新的重大的发展。其实,这种一致性衬托了当代中国外交的基本特征,或者说,形成了当代中国外交的传统。文章基于对50多年来中国外交的分析,归纳出中国外交的四个基本特征,这就是外交原则和政策的一贯性、外交目标的双重性、外交形式的多样性以及外交对象的层次性。     

一类变系数高阶线性齐次微分方程解的探求(英文)

本文对系数全为多项式和广义多项式的n阶线性齐次微分方程引入特征方程的概念。给出了具有指数型解的充要条件，推广了经典的常系数线性方程和著名的Euler方程的的解法，为求解变系数线性微分方程提供了有效的方法。     

偏微分积分方程的周期边值问题

本文用上下解方法结合特征线理论讨论了形如 U_t+f(t,x)U_x=g(t,x,u,Tu) u(0,x)=u(2π,x) (1)的一阶偏微分积分方程解的存在性与唯一性,进而用双边迭代的方法给出其求解的程序。     

Asymptotic expaxsioxs for the joint distribution of cirrelated hotellings t2 statlstics under normality

Let T² _i=z′_iS^?1z_i, i==,…k be correlated Hotelling's T² statistics under normality. where z=(z′_i,…,z′_k)′ and nS are independently distributed as N_kp((O,ρ?∑) and Wishart distribution W_p(∑, n), respectively. The purpose of this paper is to study the distribution function F(x₁,…,x_k) of (T² _i,…,T² _k) when n is large. First we derive an asymptotic expansion of the characteristic function of (T² _i,…,T² _k) up to the order n^?2. Next we give asymptotic expansions for (T² _i,…,T² _k) in two cases (i)ρ=I_k and (ii) k=2 by inverting the expanded characteristic function up to the orders n^?2 and n^?1, respectively. Our results can be applied to the distribution function of max (T² _i,…,T² _k) as a special case.     

试论满族入关前饮食文化特点

满族入关前 ,正是女真兴起时期 ,战争频仍 ,奴隶制、封建制国家不断发展的时期 ,作为特定时期的满族饮食文化表现出等级性、政策性、外来性和不断完善性等鲜明的时代特征。这些特征对入关后满族饮食文化的发展产生了深远影响 :一方面 ,其中许多因素深深积淀于满族传统饮食文化 ;另一方面 ,等级性的增强、诸种封建礼制的完备和对外来饮食文化接受 ,则为入关后满族饮食文化的进一步发展奠定了基础。     

区域的“城市性”与中国新型城市化道路

本文提出区域的“城市性”,对城市化涵义作出新的认识.考察中外城市化的演变史发现,城市化道路有两种类型:一是人口转移型城市化道路,二是结构转换型城市化道路,从中国的国情出发,借鉴中外城市化的经验教训,如今中国城市化发展道路的转型方向,应该是走人口转移和结构转型并存的“双轨”发展的新型城市化道路.     

Letter to the editor comments on Groparu-Cojocaru and Doray (2013)

Although estimating the five parameters of an unknown Generalized Normal Laplace (GNL) density by minimizing the distance between the empirical and true characteristic functions seems appealing, the approach cannot be advocated in practice. This conclusion is based on extensive numerical simulations in which a fast minimization procedure delivers deceiving estimators with values that are quite far away from the truth. These findings can be predicted by the very large values obtained for the true asymptotic variances of the estimators of the five parameters of the true GNL density.     

Bootstrap approach to test the homogeneity of order restricted mean vectors when the covariance matrices are unknown

Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are unknown, arbitrary positive definite and unequal are considered. This problem of testing has been studied to some extent, for example, by Kulatunga and Sasabuchi (1984 Kulatunga, D. D. S., Sasabuchi, S. (1984). A test of homogeneity of mean vectors against multivariate isotonic alternatives. Mem Fac Sci, Kyushu Univ Ser A Mathemat 38:151–161. [Google Scholar]) when the covariance matrices are known and also Sasabuchi et al. (2003 Sasabuchi, S., Tanaka, K., Tsukamodo, T. (2003). Testing homogeneity of multivariate normal mean vectors under an order restriction when the covariance matrices are common but unknown. Annals of Statistics. 31(5):1517–1536.[Web of Science ®] , [Google Scholar]) and Sasabuchi (2007 Sasabuchi, S. (2007). More powerful tests for homogeneity of multivariate normal mean vectors under an order restriction. Sankhya 69(4):700–716. [Google Scholar]) when the covariance matrices are unknown but common. In this paper, a test statistic is proposed and because of the main advantage of the bootstrap test is that it avoids the derivation of the complex null distribution analytically, a bootstrap test statistic is derived and since the proposed test statistic is location invariance the bootstrap p-value defined logical and some steps are presented to estimate it. Our numerical studies via Monte Carlo simulation show that the proposed bootstrap test can correctly control the type I error rates. The power of the test for some of the p-dimensional normal distributions is computed by Monte Carlo simulation. Also, the null distribution of test statistic is estimated using kernel density. Finally, the bootstrap test is illustrated using a real data.