构建社会主义和谐社会符合穆斯林的宗教信仰和根本利益

和谐是人类普遍的追求,是历史发展的永恒主题。实现社会和谐,建设美好社会,是世界上各民族、各宗教孜孜以求的共同社会理想。现在党和国家提出构建社会主义和谐社会,那么中国穆斯林这样一个信仰伊斯兰教的中华民族的组成群体如何在构建和谐社会的过程中发挥自己的作用,作出应有的贡献?本文以宗教和社会主义相适应,各民族携手共建和谐社会这个角度,从对和谐社会的理解和认识、伊斯兰教的和谐观、中国穆斯林应该为构建社会主义和谐社会这一共同目标而不懈努力三个方面探讨了伊斯兰教和穆斯林群众对构建社会主义和谐社会应有的认识、态度及实践。     

山西省生猪产品竞争力比较分析

养猪业是农村经济的重要组成部分,是畜牧业的主导。山西省地处黄土高原,有发展养猪业的资源优势。运用简单比较法,对山西省生猪产品在不同的饲养方式下与全国生猪产品在同种饲养方式下进行对比分析,揭示了山西省生猪产品生产在成本、价格、收益方面与全国同指标(平均)水平对比的优(劣)势状况,畜产品质量安全状况,并提出提升山西省生猪产品竞争力的对策建议。     

Statistical inference for the effect of magnetic brain stimulation on a motoneurone

A stochastic model is developed for the possible excitatory and inhibitory effects of a stimulus to the brain on the activity of single human motoneurones. The model consists of a Wiener process for the build-up of underlying potential, a deterministic effect due to the stimulus and a random lag from brain to muscle. Direct likelihood inference for its parameters seems impossible, and we study the use of simulation to estimate the log-likelihood for the parameters of substantive interest. Monte Carlo methods yield point and confidence interval estimates of the membrane excitability underlying excitatory and inhibitory effects. The main qualitative conclusion is that both excitatory and inhibitory effects are unambiguously present. The contribution of statistical analysis to this problem is to provide accurate and apparently reliable inference for the quantities of neurophysiological interest. More generally, our methodology has the potential to make accurate likelihood-based inferences in challenging problems, but the computational burden can be large, particularly if the model is not fully adequate for the data, as in our application.     

On Block Ordering of Variables in Graphical Modelling

Abstract.  In graphical modelling, the existence of substantive background knowledge on block ordering of variables is used to perform structural learning within the family of chain graphs (CGs) in which every block corresponds to an undirected graph and edges joining vertices in different blocks are directed in accordance with the ordering. We show that this practice may lead to an inappropriate restriction of the search space and introduce the concept of labelled block ordering B corresponding to a family of B - consistent CGs in which every block may be either an undirected graph or a directed acyclic graph or, more generally, a CG. In this way we provide a flexible tool for specifying subsets of chain graphs, and we observe that the most relevant subsets of CGs considered in the literature are families of B -consistent CGs for the appropriate choice of B . Structural learning within a family of B -consistent CGs requires to deal with Markov equivalence. We provide a graphical characterization of equivalence classes of B -consistent CGs, namely the B - essential graphs , as well as a procedure to construct the B -essential graph for any given equivalence class of B -consistent chain graphs. Both largest CGs and essential graphs turn out to be special cases of B -essential graphs.     

Bounded Estimation in the Presence of Nuisance Parameters

The aim of this paper is to extend in a natural fashion the results on the treatment of nuisance parameters from the profile likelihood theory to the field of robust statistics. Similarly to what happens when there are no nuisance parameters, the attempt is to derive a bounded estimating function for a parameter of interest in the presence of nuisance parameters. The proposed method is based on a classical truncation argument of the theory of robustness applied to a generalized profile score function. By means of comparative studies, we show that this robust procedure for inference in the presence of a nuisance parameter can be used successfully in a parametric setting.     

Non-parametric bootstrap recycling

The double bootstrap provides diagnostics for bootstrap calculations and, if need be, appropriate adjustments. The amount of computation involved is usually considerable, and recycling provides a less computer intensive alternative. Recycling consists of using repeatedly the same samples drawn from a recycling distribution G for estimation under each first-level bootstrap distribution, rather than independently repeating the simulation and estimation steps for each of these.Recycling is successful in parametric applications of the bootstrap, as demonstrated by M.A. Newton and C.J. Geyer (J. Amer. Statist. Assoc. 89: 905–912, 1994). We show that it is bound to fail in non-parametric bootstrap applications, and suggest a modification that makes the method work. The modification consists of smoothing the first-level bootstrap distributions, with the desired consequence that this removes the zero probabilities in the multinomial distributions that define them. We also discuss efficient choices of recycling distributions, both in terms of estimator efficiency and simulation efficiency.     

论柏拉图“理念”论及其对中世纪基督教神学之影响

在柏拉图思想体系中,“理念”论是其核心,它充分彰显了古希腊人追问永恒、绝对之终极本体的渴求,尤其是其“两重世界”的划分和“善”的理念之绝对先验性和超越性以及“回忆说”表现出的一种神学倾向,与中世纪基督教思想一拍即合,为基督教中彼岸世界与上帝之“合理”存在和“光照论”提供了思想根基。在一定意义上说,柏拉图的“理念”论为中世纪基督教神学的产生提供了理论的核心。     

A note on empirical likelihoods derived from pairwise score functions

Pairwise likelihood functions are convenient surrogates for the ordinary likelihood, useful when the latter is too difficult or even impractical to compute. One drawback of pairwise likelihood inference is that, for a multidimensional parameter of interest, the pairwise likelihood analogue of the likelihood ratio statistic does not have the standard chi-square asymptotic distribution. Invoking the theory of unbiased estimating functions, this paper proposes and discusses a computationally and theoretically attractive approach based on the derivation of empirical likelihood functions from the pairwise scores. This approach produces alternatives to the pairwise likelihood ratio statistic, which allow reference to the usual asymptotic chi-square distribution and which are useful when the elements of the Godambe information are troublesome to evaluate or in the presence of large data sets with relative small sample sizes. Two Monte Carlo studies are performed in order to assess the finite-sample performance of the proposed empirical pairwise likelihoods.     

COMPARATIVE ADVANTAGE AND THE CROSS‐SECTION OF BUSINESS CYCLES

Business cycles are both less volatile and more synchronized with the world cycle in rich countries than in poor ones. We develop two alternative explanations based on the idea that comparative advantage causes rich countries to specialize in industries that use new technologies operated by skilled workers whereas poor countries specialize in industries that use traditional technologies operated by unskilled workers. (1) Because new technologies are difficult to imitate, the industries of rich countries enjoy more market power and face more inelastic product demand than those of poor countries. (2) Because skilled workers are less likely to exit employment as a result of changes in economic conditions, industries in rich countries face more inelastic labor supplies than those of poor countries. We show that either asymmetry in industry characteristics can generate cross‐country differences in business cycles that resemble those we observe in the data. (JEL: E32, FA5, F41)     

Computing Probabilities of Type I Error and Type II Error of Sequential Bayesian Procedures for Testing One-Sided Hypotheses

In this article, it is shown how to compute, in an approximated way, probabilities of Type I error and Type II error of sequential Bayesian procedures for testing one-sided null hypotheses. First, some theoretical results are obtained, and then an algorithm is developed for applying these results. The prior predictive density plays a central role in this study.