世界价格理论研究成果综述

价格理论是经济学理论的皇冠,目前最主要的价格理论有12种以上。把这些理论依照时间排序,可以发现一些价格理论之间存在亲缘关系,另一些重大理论则直接来源于经验,与前期的经济学并无明显联系。把现存的价格理论整合成一个体系,我们还发现价格理论体系的逻辑架构已经非常圆满,它是一个由萨伊家族、马克思家族与货币主义家族构成了“无、有、同”的完整逻辑体系,其间仅有少许分歧。新出现的《富国律》弥合了三者之间的分歧,通过国家零货币价格政策,力求建立起一个社会保障有力、人人充分就业、物产丰富、物价合理、全民富足的理想世界。     

基于零缺陷理念的质量成本分析

从传统质量成本的局限性出发,结合“零缺陷”理论建立新的质量成本模型。分析结果显示：损失成本的变化与生产单位的数量没有很大关系,而控制成本会随着生产单位数量的增加、经验的积累和技术的成熟而降低;零缺陷质量成本管理下,企业质量水平和质量成本的控制会出现良性循环,质量水平逐渐上升而总质量成本逐渐减低。     

论理雅各的《易经》英译

19世纪末英国传教士理雅各的易经英译对中国文化在西方世界的传播和影响起了巨大的作用,他的译本经久不衰,至今仍被西方汉学家视为易经外译的典范.本文对理雅各及其易经英译本进行探讨,旨在发现其翻译的特定思路以及译本的优势与长处,寻找其不足与误译,以利新世纪易经英译的进一步精化与更为广泛的传播.     

社会资源的动员:以农民工企业家为个案

社会资源的动员是行动者维护与扩大关系网络的主要目的。以农民工企业家的社会资源的动员过程的个案分析出发,从动态的角度分析关系网络从无到有的转变,并指出在关系网络的构建过程中,不同地位的行动者之间存在着非对称性的关系。在竞争性的关系网络中,地位比较低的行动者由于其高替代性而导致其关系网络依附于高地位者,从而呈现出一种同心圆结构。     

Analyzing propensity matched zero-inflated count outcomes in observational studies

Determining the effectiveness of different treatments from observational data, which are characterized by imbalance between groups due to lack of randomization, is challenging. Propensity matching is often used to rectify imbalances among prognostic variables. However, there are no guidelines on how appropriately to analyze group matched data when the outcome is a zero-inflated count. In addition, there is debate over whether to account for correlation of responses induced by matching and/or whether to adjust for variables used in generating the propensity score in the final analysis. The aim of this research is to compare covariate unadjusted and adjusted zero-inflated Poisson models that do and do not account for the correlation. A simulation study is conducted, demonstrating that it is necessary to adjust for potential residual confounding, but that accounting for correlation is less important. The methods are applied to a biomedical research data set.     

Bayesian zero-inflated generalized Poisson regression model: estimation and case influence diagnostics

Count data with excess zeros arises in many contexts. Here our concern is to develop a Bayesian analysis for the zero-inflated generalized Poisson (ZIGP) regression model to address this problem. This model provides a useful generalization of zero-inflated Poisson model since the generalized Poisson distribution is overdispersed/underdispersed relative to Poisson. Due to the complexity of the ZIGP model, Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the considered model. Additionally, some discussions on the model selection criteria are presented and a Bayesian case deletion influence diagnostics is investigated for the joint posterior distribution based on the Kullback–Leibler divergence. Finally, a simulation study and a psychological example are given to illustrate our methodology.     

《史记》札记

文章是作者关于中华书局标点本《史记》(1982年第2版)的读书札记,共11则,指出了该书在校勘及标点方面的若干失误。     

An empirical approach to determine a threshold for assessing overdispersion in Poisson and negative binomial models for count data

Overdispersion is a problem encountered in the analysis of count data that can lead to invalid inference if unaddressed. Decision about whether data are overdispersed is often reached by checking whether the ratio of the Pearson chi-square statistic to its degrees of freedom is greater than one; however, there is currently no fixed threshold for declaring the need for statistical intervention. We consider simulated cross-sectional and longitudinal datasets containing varying magnitudes of overdispersion caused by outliers or zero inflation, as well as real datasets, to determine an appropriate threshold value of this statistic which indicates when overdispersion should be addressed.     

JIT生产与库存管理的研究

通过对中小企业库存管理的现状与问题进行分析和探究,利用"JIT"生产和零库存管理的手段,尽可能降低库存水平、提高生产运营的效率,为企业挖掘更大利润,实现企业和社会资源充分的利用.     

Confidence intervals for the mean of a population containing many zero values under unequal‐probability sampling

In many applications, a finite population contains a large proportion of zero values that make the population distribution severely skewed. An unequal‐probability sampling plan compounds the problem, and as a result the normal approximation to the distribution of various estimators has poor precision. The central‐limit‐theorem‐based confidence intervals for the population mean are hence unsatisfactory. Complex designs also make it hard to pin down useful likelihood functions, hence a direct likelihood approach is not an option. In this paper, we propose a pseudo‐likelihood approach. The proposed pseudo‐log‐likelihood function is an unbiased estimator of the log‐likelihood function when the entire population is sampled. Simulations have been carried out. When the inclusion probabilities are related to the unit values, the pseudo‐likelihood intervals are superior to existing methods in terms of the coverage probability, the balance of non‐coverage rates on the lower and upper sides, and the interval length. An application with a data set from the Canadian Labour Force Survey‐2000 also shows that the pseudo‐likelihood method performs more appropriately than other methods. The Canadian Journal of Statistics 38: 582–597; 2010 © 2010 Statistical Society of Canada