诉说离乱与建构主体——论马来西亚华人新生代的创作

马来西亚华人新生代的崛起是20世纪90年代以来马来西亚乃至东南亚华文文坛的重要现象.马来西来华人新生代在创作中甚为繁复地诉说着离乱的过往与身世的漂泊,这不但反映了他们成长期所经受的国族认同危机,而且透露出他们试图通过离乱历史的叙事而建构其马来西亚"国境内少数民族形象"的族群意识.但这种建构虽然以寻求认同为旨归,却天然地和当局打造马来西亚国族共同体的意识形态相冲突,而这冲突的双方在当前全球化语境中似乎又共同面临本真性幻觉的困境.     

代焦虑与创伤记忆--读君特·格拉斯的《狗年月》

《狗年月》是格拉斯的但泽三部曲之一部,这部作品与其他两部相比,作者的视野更加开阔.本文集中于分析小说中的"代现象",并以此为基点讨论德意志保守主义传统与纳粹统治的关系,揭示在高度分化的现代社会,不同群体之间的隔膜与争执,进而讨论如何承担历史责任的主题.     

第三代领导人对党的执政规律的探索与贡献

国际国内形势的新变化对我党的执政能力提出了严峻考验,不断探索党的执政规律成为新时期党的建设的一个重要课题。以江泽民同志为核心的第三代领导人全面客观地提出了依法治国和以德治国相结合的治国方略,是对党的执政方式的崭新探讨;与时俱进地提出了"三个代表"重要思想,对党的执政任务、执政本质、执政基础进行了深刻总结。     

Covariates and Random Effects in a Gamma Process Model with Application to Degradation and Failure

The gamma process is a natural model for degradation processes in which deterioration is supposed to take place gradually over time in a sequence of tiny increments. When units or individuals are observed over time it is often apparent that they degrade at different rates, even though no differences in treatment or environment are present. Thus, in applying gamma-process models to such data, it is necessary to allow for such unexplained differences. In the present paper this is accomplished by constructing a tractable gamma-process model incorporating a random effect. The model is fitted to some data on crack growth and corresponding goodness-of-fit tests are carried out. Prediction calculations for failure times defined in terms of degradation level passages are developed and illustrated.     

On rates of convergence to infinitely divisible laws for dependent random variables

Large O and small o approximations of the expected value of a class of functions (modified K-functional and Lipschitz class) of the normalized partial sums of dependent random variables by the expectation of the corresponding functions of infinitely divisible random variables have been established. As a special case, we have obtained rates of convergence to the Stable Limit Laws and to the Weak Laws of Large Numbers. The technique used is the conditional version of the operator method of Trotter and the Taylor expansion.     

Perfect simulation for correlated Poisson random variables conditioned to be positive

In this paper we present a perfect simulation method for obtaining perfect samples from collections of correlated Poisson random variables conditioned to be positive. We show how to use this method to produce a perfect sample from a Boolean model conditioned to cover a set of points: in W.S. Kendall and E. Thönnes (Pattern Recognition 32(9): 1569–1586, 1999), this special case was treated in a more complicated way. The method is applied to several simple examples where exact calculations can be made, so as to check correctness of the program using ²-tests, and some small-scale experiments are carried out to explore the behaviour of the conditioned Boolean model.     

Estimation of a Change Point in a Hazard Function Based on Censored Data

The hazard function plays an important role in reliability or survival studies since it describes the instantaneous risk of failure of items at a time point, given that they have not failed before. In some real life applications, abrupt changes in the hazard function are observed due to overhauls, major operations or specific maintenance activities. In such situations it is of interest to detect the location where such a change occurs and estimate the size of the change. In this paper we consider the problem of estimating a single change point in a piecewise constant hazard function when the observed variables are subject to random censoring. We suggest an estimation procedure that is based on certain structural properties and on least squares ideas. A simulation study is carried out to compare the performance of this estimator with two estimators available in the literature: an estimator based on a functional of the Nelson-Aalen estimator and a maximum likelihood estimator. The proposed least squares estimator tums out to be less biased than the other two estimators, but has a larger variance. We illustrate the estimation method on some real data sets.     

Missing at random (MAR) in nonparametric regression - A simulation experiment

The additive model is considered when some observations on x are missing at random but corresponding observations on y are available. Especially for this model, missing at random is an interesting case because the complete case analysis is expected to be no more suitable. A simulation experiment is reported and the different methods are compared based on their superiority with respect to the sample mean squared error. Some focus is also given on the sample variance and the estimated bias. In detail, the complete case analysis, a kind of stochastic mean imputation, a single imputation and the nearest neighbor imputation are discussed.     

老年人居住问题研究

在世纪之交 ,我国正快速进入人口老年化社会。本文试图通过分析我国人口老龄化的现状及问题 ,探讨解决我国人口老龄化下老年人居住问题的多方案途径。     

A generating algorithm for linear trend-free and nearly linear trend-free block designs

The theory and properties of trend-free (TF) and nearly trend-free (NTF) block designs are wel1 developed. Applications have been hampered because a methodology for design construction has not been available.

This article begins with a short review of concepts and properties of TF and NTF block designs. The major contribution is provision of an algorithm for the construction of linear and nearly linear TF block designs. The algorithm is incorporated in a computer program in FORTRAN 77 provided in an appendix for the IBM PC or compatible microcomputer, a program adaptable also to other computers. Three sets of block designs generated by the program are given as examples.

A numerical example of analysis of a linear trend-free balanced incomplete block design is provided.