Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo

We consider importance sampling (IS) type weighted estimators based on Markov chain Monte Carlo (MCMC) targeting an approximate marginal of the target distribution. In the context of Bayesian latent variable models, the MCMC typically operates on the hyperparameters, and the subsequent weighting may be based on IS or sequential Monte Carlo (SMC), but allows for multilevel techniques as well. The IS approach provides a natural alternative to delayed acceptance (DA) pseudo-marginal/particle MCMC, and has many advantages over DA, including a straightforward parallelization and additional flexibility in MCMC implementation. We detail minimal conditions which ensure strong consistency of the suggested estimators, and provide central limit theorems with expressions for asymptotic variances. We demonstrate how our method can make use of SMC in the state space models context, using Laplace approximations and time-discretized diffusions. Our experimental results are promising and show that the IS-type approach can provide substantial gains relative to an analogous DA scheme, and is often competitive even without parallelization.     

浅议高校思想政治理论课教师的高尚道德人格

本文对高校思想政治理论课教师道德人格的相关问题加以论述。     

中国金融机构的系统重要性及系统性风险传染机制分析——基于复杂网络的视角

采用最小生成树(MST)和平面极大过滤图(PMFG)方法构建和分析金融市场网络可以动态识别金融网络中节点的系统重要性,而利用最小生成树的唯一性可以全面而直观地显示系统性风险的传导机制。我们通过对银行间同业拆借市场进行的实证分析证明了该方法的有效性和稳健性,特别是最小生成树方法对系统性风险传导潜在路径的识别以及系统性风险的宏观审慎监管提供了直观而有效的手段。     

从水库移民安置看民族传统文化传承的重要性--以广西红水河梯级电站水库移民安置为例

民族传统文化是维系民族认同与团结、生存与发展的“灵魂”,它对于今天民族地区正在进行的经济建设活动,同样具有十分重要的意义。广西红水河梯级电站水库移民安置的实践,充分证明了这一点。     

Bayesian inference for the randomly censored Weibull distribution

In this paper, we consider the Bayesian inference of the unknown parameters of the randomly censored Weibull distribution. A joint conjugate prior on the model parameters does not exist; we assume that the parameters have independent gamma priors. Since closed-form expressions for the Bayes estimators cannot be obtained, we use Lindley's approximation, importance sampling and Gibbs sampling techniques to obtain the approximate Bayes estimates and the corresponding credible intervals. A simulation study is performed to observe the behaviour of the proposed estimators. A real data analysis is presented for illustrative purposes.     

论语言交际中意义协商作用的有限性

语言交际总是伴随着理解障碍。相关研究认为学习者会运用意义协商的方式来克服语言理解障碍,但是此类研究大都只涉及意义协商在克服语言理解障碍方面的积极作用。本文从社会文化和认知的角度认为,意义协商方式并不能确保所有的语言交际理解障碍得到解决,甚至有时会导致不成功的语言交际或是交际误解。因此,它对于学习者克服语言理解障碍的作用是有限的。     

影响日朝关系正常化的美国因素

日本与朝鲜间关系的发展不仅是两国出于各自利益的主观意愿,更在很大程度上受制于美国在东北亚地区的战略态度和利益。朝鲜半岛重要的地理位置不仅使其在历史上成为各大国互相争夺的焦点,也在第二次世界大战结束后成为美国遏制中国的重要战略工具。特别是在冷战结束后,美国更加重视朝鲜半岛在美国东北亚地区战略中的地位和作用。为此,美国以朝核问题为切入点,制造地区紧张气氛以维持和加强日韩对美国的军事、安全需要,同时将日朝两国关系正常化的进程纳入自己的地区战略和掌控之中,以维持美国在东北亚地区的军事存在,遏制中国。可以说,日朝两国关系正常化的进程很大程度上受制于美国在东北亚地区的战略态度和利益,也因而将是一个漫长的过程。     

探讨加强高校党校建设工作的新思路

针对高校党校建设中存在的问题,从加强高校党校建设工作的重要性和紧迫性、如何加强和改进高校党校工作等方面进行了研究,提出了提高思想认识、深化教学改革、健全规章制度、发挥互联网优势、改善办学条件和党校自身建设等办法,为加强高校党校建设工作和发展提出了新思路。     

学术期刊评价中存在的问题——学科期刊数量对期刊影响因子的影响及其改进方法

不同学科之间期刊影响因子的大小有非常大的变化,从相差数倍到相差上百倍。为探讨不同学科之间期刊影响因子有如此大差别的主要原因,使期刊影响因子既能体现学科内期刊的学术质量和影响力,也能较好地反映不同学科期刊之间的学术质量和影响力差别,本研究结合JCR数据从理论上分析了学科内期刊数量对期刊影响因子的影响。研究表明,期刊影响因子的大小随着学科内期刊数量的增加而增加,比较不同学科之间期刊影响因子的大小没有多大意义;对期刊影响因子计算方法提出了改进,改进方法较好地消除了期刊影响因子对学科内期刊数量的强烈依赖关系;改进的影响因子更客观、更有效、更合理,不仅能有效地反映期刊的学术质量和影响力,而且也使不同学科之间期刊的影响因子具有较合理的可比性。      

Robust importance sampling for some typical types of utility-based shortfall risk measures using exponential twisting and kernel density techniques

A robust algorithm for utility-based shortfall risk (UBSR) measures is developed by combining the kernel density estimation with importance sampling (IS) using exponential twisting techniques. The optimal bandwidth of the kernel density is obtained by minimizing the mean square error of the estimators. Variance is reduced by IS where exponential twisting is applied to determine the optimal IS distribution. Conditions for the best distribution parameters are derived based on the piecewise polynomial loss function and the exponential loss function. The proposed method not only solves the problem of sampling from the kernel density but also reduces the variance of the UBSR estimator.