情绪影响下群体性冲突的RDEU博弈模型分析

考虑到情绪因素对参与者行为的影响,基于等级依赖期望效用理论框架构建了群体性冲突的RDEU博弈模型,讨论了不同情绪状态下的博弈纳什均衡的存在性,分析了情绪因素对参与者选择混合策略的行为机理。研究发现:情绪因素对群体性冲突的博弈均衡有着显著的影响,当博弈参与者具有“悲观”情绪时,倾向于"对抗"性的行为,当参与者具有“乐观”情绪时,易于做出“让步”性的行为。在情绪的驱动下,参与者还会受到对方采取某个策略的判断的影响,如当弱势群体认为对手采取“压制”策略的概率低于某个分界点时,随着乐观情绪指数的增大,其选择“对抗”策略的概率将随之增大。最后,以房屋拆迁群体性冲突为例,数值分析了博弈模型的结论。     

The Changing Shape of Welfare Policy in Korea: Analysis of Break Point in the Welfare Budget

This paper aims to investigate the welfare policy change in South Korea. Based on punctuated equilibrium theory, I analyze kurtosis and break point of the distribution of variation in the general government welfare budget. As a result, the change in welfare budget levels in South Korea has been quite moderate. But two break points were set in 1977 and 1999. These cutoff points are related with the change of the Korean Welfare State and clearly distinguished from different times. That is, the characteristics of structure that were built during these two time periods have lasted until now. Specifically, the responsibility of state in welfare is narrow. And the feature of employment‐friendly welfare policy was formed in 1977. Also, the focus on livelihood security and employment in welfare spending was constructed in 1999. The analysis of budget is a useful tool in examining the policy change. We expect to find more specific characteristics of the Korean welfare state including special accounts and funds in future.     

教育实习管理模式的现代转向：从高校主导到多元共建

教育实习管理模式是实习生职业成长中的重要一环。当前,高校主导的实习管理模式已无法适应教师职前教育的要求。教育实习管理模式应该实现从高校主导到多元共建的现代转向,以适应高素质师资培养的需要。     

旅游业发展对区域经济增长影响研究

旅游业被视为区域经济发展的动力,能够增加居民收入和就业机会,并联动相关产业部门的发展。然而,旅游业发展带动经济增长的假说始终存在争议,未得到学界的一致认可。在经济增长理论框架下,采用一般均衡分析方法探讨旅游业的发展所带来的产业转移情况和居民福利效用变化,使用差分广义矩估计方法实证分析中国旅游业的发展对经济带来的影响并具体区分了旅游业发展对沿海发达省份和内陆欠发达省份的经济影响之间的差别。     

Rounding non-binary categorical variables following multivariate normal imputation: evaluation of simple methods and implications for practice

We study bias arising from rounding categorical variables following multivariate normal (MVN) imputation. This task has been well studied for binary variables, but not for more general categorical variables. Three methods that assign imputed values to categories based on fixed reference points are compared using 25 specific scenarios covering variables with k=3, …, 7 categories, and five distributional shapes, and for each k=3, …, 7, we examine the distribution of bias arising over 100,000 distributions drawn from a symmetric Dirichlet distribution. We observed, on both empirical and theoretical grounds, that one method (projected-distance-based rounding) is superior to the other two methods, and that the risk of invalid inference with the best method may be too high at sample sizes n≥150 at 50% missingness, n≥250 at 30% missingness and n≥1500 at 10% missingness. Therefore, these methods are generally unsatisfactory for rounding categorical variables (with up to seven categories) following MVN imputation.     

Sensitivity to imputation models and assumptions in receiver operating characteristic analysis with incomplete data

Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms.     

Joint models for multiple longitudinal processes and time-to-event outcome

ABSTRACT

Joint models are statistical tools for estimating the association between time-to-event and longitudinal outcomes. One challenge to the application of joint models is its computational complexity. Common estimation methods for joint models include a two-stage method, Bayesian and maximum-likelihood methods. In this work, we consider joint models of a time-to-event outcome and multiple longitudinal processes and develop a maximum-likelihood estimation method using the expectation–maximization algorithm. We assess the performance of the proposed method via simulations and apply the methodology to a data set to determine the association between longitudinal systolic and diastolic blood pressure measures and time to coronary artery disease.     

Comparing Normal Random Samples,with Uncertainty About the Priors and Utilities

Abstract. We study the problem of deciding which of two normal random samples, at least one of them of small size, has greater expected value. Unlike in the standard Bayesian approach, in which a single prior distribution and a single loss function are declared, we assume that a set of plausible priors and a set of plausible loss functions are elicited from the expert (the client or the sponsor of the analysis). The choice of the sample that has greater expected value is based on equilibrium priors, allowing for an impasse if for some plausible priors and loss functions choosing one and for others the other sample is associated with smaller expected loss.     

无线光码分多址通信系统编码技术研究

介绍了在光码分多址通信系统中常用的几种编码方式,通过分析、比较各自的优缺点,提出了一种比较适合无线光码分多址通信系统的新编码方案,称为双极性码的单极性实现     

Rethinking the nation and international relations: The space of nation states

Efforts to move sociology beyond the nation state and international relations theory have both been plagued by several limitations and dualisms. Recent research has begun to find ways beyond the problems by turning to Pierre Bourdieu's relational conception of social structure and practice. Yet one specific relational structure forming a key part of the puzzle has been neglected or merely implicitly assumed so far: the space of nation states. After clarifying the structural-constructivist nature of this concept, we aim to specify it by constructing an empirical model of the contemporary space of nation states using a specially compiled dataset and tools of geometric data analysis. The analysis reveals the distribution of powers on the world scene, and more specifically, the uneven possession of two varieties of “meta-capital” understood as capacities to regulate the value and exchangeability of certain capitals and to decree what even defines a legitimate “state”. We argue that the nation state, which is accurately understood as a contingent construct and well-founded fiction from a Bourdieusian viewpoint, should not be excluded when analyzing the expression and reproduction of contemporary global power relations.