基于SBU链接概念的多元化动力模型

基于SBU链接概念,并考虑其它理论对企业多元化所做出的解释,本文提出一个新的企业多元化动力模型。此模型,第一,不但可以较好地阐释企业相关多元化与不相关多元化行为,还为企业重聚主业、瘦身和重构等行为找到了理论依据;第二,比较简单,只有三个基本元素:企业剩余能力、市场机会和链接;第三,揭示了企业发展的内在平衡机制———获取协同效应与躲避共同威胁之间的权衡。     

朝鲜义勇军的活动与中国朝鲜族历史的联系

朝鲜义勇军的前身是朝鲜义勇队,基本队员是东北朝鲜族青年,其主力转移到太行山后,改组为朝鲜义勇军,配合八路军抗战。根据形势发展,在延安组建了延安朝鲜革命军政学校,优秀的朝鲜族革命干部承担主要的领导和培养工作。日本投降后,朝鲜义勇军挺进东北,一部去朝鲜,剩下的被编成三个支队,在朝鲜族聚居区进行活动,促进了朝鲜族社会历史的发展。     

对规范行政执法的思考--兼谈行政执法与刑事执法的衔接

规范行政执法,应从广义理解,其既包括行政机关依法作出的行政行为必须具备胜诉的三个条件,即能够经得住法院的评判,最终被认定为行为合法;又包括行政机关在行政执法过程发现有刑事犯罪嫌疑,依法将案件移送公安、检察机关。但专家、学者的目光多聚焦在前者,鲜有对后者进行详细考察论证的,而后者在实践中又存在诸多问题,因此,有必要对这一问题进行研究,找出原因,以真正实现依法行政。     

Identifiability and bias reduction in the skew-probit model for a binary response

The skew-probit link function is one of the popular choices for modelling the success probability of a binary variable with regard to covariates. This link deviates from the probit link function in terms of a flexible skewness parameter. For this flexible link, the identifiability of the parameters is investigated. Next, to reduce the bias of the maximum likelihood estimator of the skew-probit model we propose to use the penalized likelihood approach. We consider three different penalty functions, and compare them via extensive simulation studies. Based on the simulation results we make some practical recommendations. For the illustration purpose, we analyse a real dataset on heart-disease.     

中、高职“数控编程”课程教学衔接研究

数控编程课程是中、高职数控专业中重要的核心专业课。在分析中、高职数控编程课程衔接现状基础上,提出了对该课程的标准化,以期提高教学质量,确保数控专业高素质高技能人才的培养。     

Automatic Bayesian quantile regression curve fitting

Quantile regression, including median regression, as a more completed statistical model than mean regression, is now well known with its wide spread applications. Bayesian inference on quantile regression or Bayesian quantile regression has attracted much interest recently. Most of the existing researches in Bayesian quantile regression focus on parametric quantile regression, though there are discussions on different ways of modeling the model error by a parametric distribution named asymmetric Laplace distribution or by a nonparametric alternative named scale mixture asymmetric Laplace distribution. This paper discusses Bayesian inference for nonparametric quantile regression. This general approach fits quantile regression curves using piecewise polynomial functions with an unknown number of knots at unknown locations, all treated as parameters to be inferred through reversible jump Markov chain Monte Carlo (RJMCMC) of Green (Biometrika 82:711–732, 1995). Instead of drawing samples from the posterior, we use regression quantiles to create Markov chains for the estimation of the quantile curves. We also use approximate Bayesian factor in the inference. This method extends the work in automatic Bayesian mean curve fitting to quantile regression. Numerical results show that this Bayesian quantile smoothing technique is competitive with quantile regression/smoothing splines of He and Ng (Comput. Stat. 14:315–337, 1999) and P-splines (penalized splines) of Eilers and de Menezes (Bioinformatics 21(7):1146–1153, 2005).     

Second-order least squares estimation of censored regression models

This paper proposes the second-order least squares estimation, which is an extension of the ordinary least squares method, for censored regression models where the error term has a general parametric distribution (not necessarily normal). The strong consistency and asymptotic normality of the estimator are derived under fairly general regularity conditions. We also propose a computationally simpler estimator which is consistent and asymptotically normal under the same regularity conditions. Finite sample behavior of the proposed estimators under both correctly and misspecified models are investigated through Monte Carlo simulations. The simulation results show that the proposed estimator using optimal weighting matrix performs very similar to the maximum likelihood estimator, and the estimator with the identity weight is more robust against the misspecification.     

邓小平社会主义本质论与社会主义核心价值观的内在联系

邓小平社会主义本质论和社会主义核心价值观是实现中华民族伟大复兴道路上的时代产物,它们是一脉相承的。邓小平社会主义本质论和社会主义核心价值观既为建设社会主义现代化国家提供了理论方向,又推动了社会各项事业的和谐发展。因此,深化对社会主义本质论的认识,更好地把握社会主义核心价值观,就必须深刻理解两者的内在联系。     

On the maximization of likelihoods belonging to the exponential family using a Levenberg–Marquardt approach

The Levenberg–Marquardt algorithm is a flexible iterative procedure used to solve non-linear least-squares problems. In this work, we study how a class of possible adaptations of this procedure can be used to solve maximum-likelihood problems when the underlying distributions are in the exponential family. We formally demonstrate a local convergence property and discuss a possible implementation of the penalization involved in this class of algorithms. Applications to real and simulated compositional data show the stability and efficiency of this approach.