我国地方政府制度创新的路径选择

从分析我国地方政府制度创新的动因入手，着重从三个方面讨论了我国地方政府制度创新的路径，即地方政府应履行自己的产权职能，以制度创新促进产权的多元化，并通过产权保护，解决微观主体的动力激励问题；以制度化规范中央与地方的制度创新关系；退出市场职能领域，实现制度创新的范式转换。     

New methods for fitting multiple sinusoids from irregularly sampled data

A novel framework is proposed for the estimation of multiple sinusoids from irregularly sampled time series. This spectral analysis problem is addressed as an under-determined inverse problem, where the spectrum is discretized on an arbitrarily thin frequency grid. As we focus on line spectra estimation, the solution must be sparse, i.e. the amplitude of the spectrum must be zero almost everywhere. Such prior information is taken into account within the Bayesian framework. Two models are used to account for the prior sparseness of the solution, namely a Laplace prior and a Bernoulli–Gaussian prior, associated to optimization and stochastic sampling algorithms, respectively. Such approaches are efficient alternatives to usual sequential prewhitening methods, especially in case of strong sampling aliases perturbating the Fourier spectrum. Both methods should be intensively tested on real data sets by physicists.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

对地方工科大学开展"双语教学"的认识

随着社会经济形势的发展,中国迫切需要大批了解世界各国文化、科技的高素质人才,高校开展双语教学,是积极主动适应这一社会需要的重要举措.文章分析了地方工科大学开展双语教学的意义和所面临的问题,并就如何提高双语教学的效果提出一些看法.     

新微派建筑初探

文章探讨了新徽派建筑的类型和特征,对新徽派建筑的作品进行了评析。分析了20世纪80年代以来新徽派建筑的四条主要探索途径及成因,着重论述了它推陈出新的内涵和美学特征以及对新地方风格建筑探索的启示意义。     

发展用户驻地网与打破本地固话垄断

本文提出了一个发展用户驻地网的思路,着重论述了发展用户驻地网可有效地打破本地固话垄断,兼述了发展驻地网对电信管制的影响及发展驻地网所需解决的问题。     

A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.     

太平天国乡官的任用标准与社会功效

对太平天国乡官制度的研究,传统的阶级分析论观点过分拘泥在乡官的阶级成分上,并以此为基础判定政权的性质。其实,以历史当事人的视角去认识当时的政策,是一种更客观的研究角度。太平天国任用乡官的标准,是建立在太平天国地方行政的政治需要之上的。出于以征收粮赋为重点的传统地方行政的需要,太平天国着意与精通传统行政事务的地方名流合作。从社会功效角度来看,太平天国当局通过发挥地方人士的行政优势,很好地弥补了自身行政经验的不足,成功影响了地方政治,并有效缓冲了自身对农村社会的冲击。     

Markov Properties for Acyclic Directed Mixed Graphs

We consider acyclic directed mixed graphs, in which directed edges ( x → y ) and bi-directed edges ( x ↔ y ) may occur. A simple extension of Pearl's d -separation criterion, called m -separation, is applied to these graphs. We introduce a local Markov property which is equivalent to the global property resulting from the m -separation criterion for arbitrary distributions.     

On Rates of Convergence for Bayesian Density Estimation

Abstract.  We consider the problem of estimating a compactly supported density taking a Bayesian nonparametric approach. We define a Dirichlet mixture prior that, while selecting piecewise constant densities, has full support on the Hellinger metric space of all commonly dominated probability measures on a known bounded interval. We derive pointwise rates of convergence for the posterior expected density by studying the speed at which the posterior mass accumulates on shrinking Hellinger neighbourhoods of the sampling density. If the data are sampled from a strictly positive, α -Hölderian density, with α  ∈ ( 0,1] , then the optimal convergence rate n^{− α / (2 α +1)} is obtained up to a logarithmic factor. Smoothing histograms by polygons, a continuous piecewise linear estimator is obtained that for twice continuously differentiable, strictly positive densities satisfying boundary conditions attains a rate comparable up to a logarithmic factor to the convergence rate n ^−4/5 for integrated mean squared error of kernel type density estimators.