手机媒体发布政府信息的成本分析

手机媒体为政府信息公开提供了一种全新的方式,尽管它拥有便捷性的优势,但利用手机媒体发布政府信息也会产生巨大的成本。政府信息发布是一项利国利民的好事,不能仅由政府承担或由公众个人承担。从手机媒体发布政府信息成本产生的根源入手,分析了各项成本的来源及主要用途,提出了由政府主导,运营商及公众个人相互配合的成本承担方式,同时也揭示了其中的存在的问题,并提出了相关对策。     

关于正算子积逼近的几个结果

给出了算子Ｔ∈Ｂ（ Ｈ） 在极分解下属于Ｐ３ 的充要条件，正常算子Ｔ 属于Ｐ２ 时的一些性质，以及张量积算子ＡＢ 属于Ｐｎ 的充要条件     

拟脐超曲面中的稳定积分流

设Ｎｎ是常曲率空间Ｍｎ＋１（ｃ）中的紧致拟脐超曲面．证明了在一些几何条件下，Ｎｎ中不存在ｐ－维稳定积分流，相应地，Ｎｎ的ｐ－维同调群消没．     

四阶Laguerre型微分方程的左定空间和左定算子

本文讨论了某四阶Laguerre型微分方程的下有界性，并构造了相关的左定空间和左定算子．     

特殊无穷维矩阵Hamilton算子的探讨

本文在原有标量Hamilton算子的基础上,分别构造且证明了三类不同阶数的矩阵Hamilton算子的形式,并得到这些算子与已给定的Hamilton算子形成了三个特殊Hamilton算子对的结论.     

市场、国家与经营者自由——反垄断法的经济伦理学批判

反垄断法是市场经济的国家干预法。它提供给人们的思考是,意图通过国家干预手段达到资源优化配置作用的效果是否会优于市场机制本身?为之,经济学理论研究却提供了两种截然相反的结论。但问题是,如果国家干预优于市场机制本身,那么市场机制还有存在的必要吗?如果不是,那么市场的自生自发秩序如何塑造,作为市场主体之一经营者的自由权利最大可以扩展到什么范围,国家规制垄断的合理边界该如何限定?     

电信运营企业节能指标分解模型研究

从单位业务耗电量偏离度和节电量占比两个维度建立节能潜力-意愿矩阵,利用主成分分析和分层聚类分析将分公司按照节能潜力和意愿的高低细分为4类。提出结合非参数检验、回归分析、单位业务耗电量分解和节电量分解方法的节能指标分解模型。通过分析计算将某省电信运营企业下辖21个分公司分类,并提出不同类别的分公司的节能指标。     

Testing the Equality of Covariance Operators in Functional Samples

Abstract. We propose a non‐parametric test for the equality of the covariance structures in two functional samples. The test statistic has a chi‐square asymptotic distribution with a known number of degrees of freedom, which depends on the level of dimension reduction needed to represent the data. Detailed analysis of the asymptotic properties is developed. Finite sample perfo‐rmance is examined by a simulation study and an application to egg‐laying curves of fruit flies.     

Strategies for Fitting Large,Geostatistical Data in MCMC Simulation

Models for geostatistical data introduce spatial dependence in the covariance matrix of location-specific random effects. This is usually defined to be a parametric function of the distances between locations. Bayesian formulations of such models overcome asymptotic inference and estimation problems involved in maximum likelihood-based approaches and can be fitted using Markov chain Monte Carlo (MCMC) simulation. The MCMC implementation, however, requires repeated inversions of the covariance matrix which makes the problem computationally intensive, especially for large number of locations. In the present work, we propose to convert the spatial covariance matrix to a sparse matrix and compare a number of numerical algorithms especially suited within the MCMC framework in order to accelerate large matrix inversion. The algorithms are assessed empirically on simulated datasets of different size and sparsity. We conclude that the band solver applied after ordering the distance matrix reduces the computational time in inverting covariance matrices substantially.     

Local Convergence Rate of Mean Squared Error in Density Estimation

The local convergence rate of a multivariate density estimators based on the certain delta-sequence is studied. In contrast to known results, the conditions on the density are formulated in terms of the modulus of continuity. The main contribution of this study is relaxing the corresponding smoothing conditions in terms of arbitrary modulus of continuity type majorant. In particular, when the density f ∈ L ^p (R ^d ) satisfies Lipschitz condition of order γ = 1 at x, the rate of convergency contains terms with logarithm, which is the best possible convergency rate.