走向柳宗元接受史研究

接受理论充分肯定了读者在文学系统中的重要地位,开辟了文学研究的新领域。柳宗元是一个具有旺盛生命力的文学家,其作品接受史的内容丰富多彩。对柳宗元的接受史进行研究,是一门有着丰厚内涵的课题。在走向柳宗元接受史研究的进程中,须掌握相关的理论,洞悉研究的现状,做好研究的策略。     

On the Fisher–Bingham distribution

This paper primarily is concerned with the sampling of the Fisher–Bingham distribution and we describe a slice sampling algorithm for doing this. A by-product of this task gave us an infinite mixture representation of the Fisher–Bingham distribution; the mixing distributions being based on the Dirichlet distribution. Finite numerical approximations are considered and a sampling algorithm based on a finite mixture approximation is compared with the slice sampling algorithm.     

ESTIMATION IN RICKER'S TWO-RELEASE METHOD: A BAYESIAN APPROACH

The Ricker's two‐release method is a simplified version of the Jolly‐Seber method, from Seber's Estimation of Animal Abundance (1982) , used to estimate survival rate and abundance in animal populations. This method assumes there is only a single recapture sample and no immigration, emigration or recruitment. In this paper, we propose a Bayesian analysis for this method to estimate the survival rate and the capture probability, employing Markov chain Monte Carlo methods and a latent variable analysis. The performance of the proposed method is illustrated with a simulation study as well as a real data set. The results show that the proposed method provides favourable inference for the survival rate when compared with the modified maximum likelihood method.     

海洋法系中单双诺合同初探

单双诺合同作为海洋法系中的一种合同分类,是根据合同成立时待履行的允诺的数目而划分的。海洋法系中通过案例及制定法确定的有关这类合同的规则,对于大陆法系合同争议的解决也有相当的借鉴意义。其中合同的承诺方式、成立时间及履行方式等问题的规定对合同效力尤为重要。     

论古代小说批评对史学"实录"意识的接受

中国古代小说具有崇实黜虚的民族特征,表现在对史学“实录”意识的接受。从文学接受角度看,中国古代小说批评在接受史学“实录”意识的历程中呈现出一定的时代特征。这种现象的发生,有其深刻的文化原因。     

试论当代文化思潮影响下的中国文学接受

文学接受受文艺思潮影响甚大。当代,由于文艺政策的不同,引起创作和理论发生转换,由此导致近半个世纪的文学接受呈现出一种独特的景象即从接受动机来看,现实主义接受是当代文学接受的主潮;从期待视野来看,当代文学接受主潮的主题意蕴由宏大走向私人化;从文化传播来看,当代文学接受呈现出由封闭、一元、被动到开放、多元、主动。正是接受与创作主体的互动关系,推动着文学不断向前,从而使当代文学呈现出一种更加契合时代精神的、更加符合文学和人的内涵的新的面貌。     

Conditioning on Auxiliary Variable Means in Finite Population Inference

This paper reviews conditional properties of the mean and total estimators of a finite population when auxiliary information is available. An exact design-based conditional analysis for complex sampling designs is intractable, but an asymptotic conditional framework can be developed. Within such a framework the paper establishes sufficient conditions for conditional unbiasedness and explores conditional properties of various types of regression estimators. A sample statistic capable of indicating the presence of substantial conditional biases is proposed, and illustrated by a simulation study.     

Hyper Inverse Wishart Distribution for Non-decomposable Graphs and its Application to Bayesian Inference for Gaussian Graphical Models

While conjugate Bayesian inference in decomposable Gaussian graphical models is largely solved, the non-decomposable case still poses difficulties concerned with the specification of suitable priors and the evaluation of normalizing constants. In this paper we derive the DY-conjugate prior ( Diaconis & Ylvisaker, 1979 ) for non-decomposable models and show that it can be regarded as a generalization to an arbitrary graph G of the hyper inverse Wishart distribution ( Dawid & Lauritzen, 1993 ). In particular, if G is an incomplete prime graph it constitutes a non-trivial generalization of the inverse Wishart distribution. Inference based on marginal likelihood requires the evaluation of a normalizing constant and we propose an importance sampling algorithm for its computation. Examples of structural learning involving non-decomposable models are given. In order to deal efficiently with the set of all positive definite matrices with non-decomposable zero-pattern we introduce the operation of triangular completion of an incomplete triangular matrix. Such a device turns out to be extremely useful both in the proof of theoretical results and in the implementation of the Monte Carlo procedure.     

Median Estimation Using Double Sampling

This paper proposes a general class of estimators for estimating the median in double sampling. The position estimator, stratification estimator and regression type estimator attain the minimum variance of the general class of estimators. The optimum values of the first-phase and second-phase sample sizes are also obtained for the fixed cost and the fixed variance cases. An empirical study examines the performance of the double sampling strategies for median estimation. Finally, an extension of the methods of Chen & Qin (1993) and Kuk & Mak (1994) is considered for the double sampling strategy.     

Bias-Corrected Moment-Based Estimators for Parametric Models Under Endogenous Stratified Sampling

This paper provides an integrated approach for estimating parametric models from endogenous stratified samples. We discuss several alternative ways of removing the bias of the moment indicators usually employed under random sampling for estimating the parameters of the structural model and the proportion of the strata in the population. Those alternatives give rise to a number of moment-based estimators that are appropriate for both cases where the marginal strata probabilities are known and unknown. The derivation of our estimators is very simple and intuitive and incorporates as particular cases most of the likelihood-based estimators previously suggested by other authors.