A Bayesian Meta-Modeling Approach for Gaussian Stochastic Process Models Using a Non Informative Prior

In this article, an efficient Bayesian meta-modeling approach is proposed for Gaussian stochastic process models in computer experiments. Different prior densities and particularly, a non informative hyper prior have been employed on the parameters involved in the correlation matrix. And the estimation of related parameters is obtained by the expectation-maximization algorithm. Compared with the recent work of Li and Sudjianto (2005 Li , R. , Sudjianto , A. ( 2005 ). Analysis of computer experiments using penalized likelihood in Kriging models . Technometrics 47 : 111 – 120 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), the proposed approach is not only of higher prediction accuracy but also of lower computational cost, due to the utilization of the non informative prior and the absence of tuning parameters. Experimental results demonstrate that our approach yields state-of-the-art performance.     

Coherent Frequentism: A Decision Theory Based on Confidence Sets

By representing fair betting odds according to one or more pairs of confidence set estimators, dual parameter distributions called confidence posteriors secure the coherence of actions without any prior distribution. This theory reduces to the maximization of expected utility when the pair of posteriors is induced by an exact or approximate confidence set estimator or when a reduction rule is applied to the pair. Unlike the p-value, the confidence posterior probability of an interval hypothesis is suitable as an estimator of the indicator of hypothesis truth since it converges to 1 if the hypothesis is true or to 0 otherwise.     

机构投资者异质性的上市公司股利政策研究

 本文从现金股利政策的角度来研究机构投资者的投资行为和参与上市公司治理的情况。首先回顾了该方面的相关文献,以信号理论为基础,分析机构投资者与现金股利政策可能存在的关系;接着对机构投资者的基本特征以及我国机构投资者和上市公司现金股利政策的概况及特点进行了总结;最后本文以 2007至2010 年的机构投资者持股数据与上市公司现金股利政策数据进行统计分析、回归分析,实证检验了机构投资者异质性与上市公司股利政策之间的关系。     

Parameter estimation of nonlinear mixed-effects models using first-order conditional linearization and the EM algorithm

Nonlinear mixed-effects (NLME) models are flexible enough to handle repeated-measures data from various disciplines. In this article, we propose both maximum-likelihood and restricted maximum-likelihood estimations of NLME models using first-order conditional expansion (FOCE) and the expectation–maximization (EM) algorithm. The FOCE-EM algorithm implemented in the ForStat procedure SNLME is compared with the Lindstrom and Bates (LB) algorithm implemented in both the SAS macro NLINMIX and the S-Plus/R function nlme in terms of computational efficiency and statistical properties. Two realworld data sets an orange tree data set and a Chinese fir (Cunninghamia lanceolata) data set, and a simulated data set were used for evaluation. FOCE-EM converged for all mixed models derived from the base model in the two realworld cases, while LB did not, especially for the models in which random effects are simultaneously considered in several parameters to account for between-subject variation. However, both algorithms had identical estimated parameters and fit statistics for the converged models. We therefore recommend using FOCE-EM in NLME models, particularly when convergence is a concern in model selection.     

An efficient algorithm for finding the M most probable configurationsin probabilistic expert systems

A probabilistic expert system provides a graphical representation of a joint probability distribution which enables local computations of probabilities. Dawid (1992) provided a flow- propagation algorithm for finding the most probable configuration of the joint distribution in such a system. This paper analyses that algorithm in detail, and shows how it can be combined with a clever partitioning scheme to formulate an efficient method for finding the M most probable configurations. The algorithm is a divide and conquer technique, that iteratively identifies the M most probable configurations.     

我国企业财务管理的目标

通过系统论证,提出我国企业财务管理目标是业主财富最大化而非利润最大化。     

戈德尔的市场自由道德理论评介

戴卫·戈德尔是继罗尔斯之后 ,对契约主义思想影响最大 ,同时也带来了最多争议的思想家之一。他从塑造理想市场的需要出发界说人的道德与理性 ,认为二者同市场的运行原则———有限制最大化是和谐一致的。道德与理性的一致性假设虽然能够有效解决市场分析中的市场失灵问题 ,但是 ,这一假设本身依赖于一个理想市场的优先存在。两个假设的相互依赖最终使得戈德尔的道德学说陷入了解释学的循环     

“刘易斯转折点”假象及其对“人口红利”释放的冲击

本文分析了当前普遍范围的用工荒是由于实际工资低于保留工资引起的农民工用脚投票结果。在此利用新家庭经济学单一模型理论分析这种经济行为是与简单单一个体预期效用最大化的经济行为相区别;农户以家庭为单位在金融资本及现代教育人力资本短缺的情况下通过家庭成员劳动力资本对外投资实施风险规避,在家庭内部实现收入分享,风险共担。这种经济行为带来的在工业制造和农业无法有效释放人口红利的结果,最终导致用工荒和环境负外部性以资本替代劳动的现代农业生产。     

结构转变、制度变迁下的人口红利与经济增长

已有的对人口红利影响经济增长的实证研究未将结构和制度的重大变革纳入模型,这与东亚及我国经济增长的现实不符。本文通过在模型中纳入结构转变和制度变迁变量,用1978～2008年的数据进行误差修正分析,计算出在结构转变和制度变迁的背景下,我国人口红利及各要素对经济增长的影响。结果发现,固定资产投资对我国经济增长的影响程度最大,其次是技术进步,第三是制度变迁,结构变化的影响也很显著。人口红利的影响也较显著,但是其对经济增长解释力度较小。因此随着人口红利的逐渐消失,未来的经济增长更需要依靠投资、技术进步、结构变迁和制度变革。     

人口结构转型、市场化与国际产业转移的叠加效应分析——对中国“人口红利”的新解读

对于我国经济持续30年高速增长这一举世瞩目的经济现象,本文试图寻找中国因素加以解释,认为中国两次特殊的人口政策导致的劳动人口扩张只有在“市场化”与“国际产业转移”同步条件下才能转化为“人口红利’’并支撑中国经济近30多年持续高速增长。本文通过建立多元回归模型验证了我们提出的经验性假说。