电力系统整体可靠性研究

提出了利用Monte-Carlo模拟算法计算电力系统整体可靠性的方法．建立了电力系统运作过程的数学描述模型以及影响电力系统可靠性因素的概率模型，给出了上海市2002年电力系统整体可靠性的模拟计算结果，指出了该计算方法在系统评估和系统规划方面的应用前景．     

论管理中的小概率事件

小概率事件的存在、发展变化,是不以人的意志为转移的。但是人们根本没有有针对性地对其本质,规律性及内在联系开展过研究。介绍了小概率事件的含义、现象、性质及其规律,提出了防控措施,特别是针对管理中的小概率问题,进行了深层次的剖析。     

我国通货膨胀率的动态波动机制及政策启示

本文应用Markov区制转移模型研究了1987-2008年2月我国通货膨胀率的动态波动路径。研究结果表明,我国通货膨胀波动存在显著的三区制特征:低通胀区制、温和通胀区制和高通胀区制。同时,得到了以下结论:(1)我国的通货膨胀在大部分时期都处于低通胀或温和通胀区制;(2)我国的通胀惯性在低通胀区制较低,在温和通胀和高通胀区制较高(接近于1),因此我国的经济政策应具有前瞻性;(3)三区制Markov区制转移模型能较好地刻画我国近20年来的高通胀事件,因此本模型也可以用于通胀预警机制的研究。     

How many people participated in candlelight protests? Counting the size of a dynamic crowd

The recent controversy about the size of crowds at candlelight protests in Korea raises an interesting question regarding the methods used to estimate crowd size. Protest organizers tend to count all participants in the event from its start to finish, while the police usually report the crowd size at its peak. While several counting methods are available to estimate the size of a crowd at a given time, counting the total number of the participants at a protest is not straightforward. In this paper, we propose a new estimator to count the total number of participants that we call the size of a dynamic crowd. We assume that the arrival and departure times of the crowd are randomly observed and that the number of the attendees in the crowd at a specific time is estimable. We estimate the number of total attendees during the entire gathering based on the capture-recapture model. We also propose a bootstrap procedure to construct a confidence interval for the crowd size. We demonstrate the performance of the proposed method with simulation studies and the data from Korea''s March for Science, a global event across the world on Earth Day, April 22, 2017.     

系统状态概率矩阵在企业集群中的应用

阐述了马尔可夫决策理论中的最基本分析方法———系统状态转移概率矩阵决策法,针对企业集群的特点,运用系统状态转移概率矩阵决策法对企业集群市场的状态进行了分析,并对各种状态的未来分布趋势和分布状况进行预测,分别计算出各种类型企业的未来市场资源份额,给政府进行市场的调节提供了理论上的依据和方法上的指导。     

带干扰的双险种Cox风险模型

给出了一个较一般的风险模型即带干扰的双险种Cox风险模型,并运用鞅的方法得出了保险公司的最终破产概率ψ(u)的不等式,使得用它来研究保险公司的盈利更符合实际情况,更具有实际意义.     

Upper probabilities based only on the likelihood function

In the problem of parametric statistical inference with a finite parameter space, we propose some simple rules for defining posterior upper and lower probabilities directly from the observed likelihood function, without using any prior information. The rules satisfy the likelihood principle and a basic consistency principle ('avoiding sure loss'), they produce vacuous inferences when the likelihood function is constant, and they have other symmetry, monotonicity and continuity properties. One of the rules also satisfies fundamental frequentist principles. The rules can be used to eliminate nuisance parameters, and to interpret the likelihood function and to use it in making decisions. To compare the rules, they are applied to the problem of sampling from a finite population. Our results indicate that there are objective statistical methods which can reconcile three general approaches to statistical inference: likelihood inference, coherent inference and frequentist inference.     

Simultaneous Credible Bands for Latent Gaussian Models

Abstract. Deterministic Bayesian inference for latent Gaussian models has recently become available using integrated nested Laplace approximations (INLA). Applying the INLA‐methodology, marginal estimates for elements of the latent field can be computed efficiently, providing relevant summary statistics like posterior means, variances and pointwise credible intervals. In this article, we extend the use of INLA to joint inference and present an algorithm to derive analytical simultaneous credible bands for subsets of the latent field. The algorithm is based on approximating the joint distribution of the subsets by multivariate Gaussian mixtures. Additionally, we present a saddlepoint approximation to compute Bayesian contour probabilities, representing the posterior support of fixed parameter vectors of interest. We perform a simulation study and apply the given methods to two real examples.     

重构我国民事诉讼证明标准

证明标准是证据法中重要而又难以把握的问题。认为我国民事案件应该采用法律真实的证明标准而不是客观真实的证明标准。而法律真实证明标准又可分为优势证据证明标准和高度盖然性证明标准。根据人们认识事物常态和现阶段的法律状况等因素,认为我国民事案件应该采用高度盖然性证明标准,在采用高度盖然性证明标准过程中有些事项需要予以注意。     

Probability Elicitation Under Severe Time Pressure: A Rank‐Based Method

Probability elicitation protocols are used to assess and incorporate subjective probabilities in risk and decision analysis. While most of these protocols use methods that have focused on the precision of the elicited probabilities, the speed of the elicitation process has often been neglected. However, speed is also important, particularly when experts need to examine a large number of events on a recurrent basis. Furthermore, most existing elicitation methods are numerical in nature, but there are various reasons why an expert would refuse to give such precise ratio‐scale estimates, even if highly numerate. This may occur, for instance, when there is lack of sufficient hard evidence, when assessing very uncertain events (such as emergent threats), or when dealing with politicized topics (such as terrorism or disease outbreaks). In this article, we adopt an ordinal ranking approach from multicriteria decision analysis to provide a fast and nonnumerical probability elicitation process. Probabilities are subsequently approximated from the ranking by an algorithm based on the principle of maximum entropy, a rule compatible with the ordinal information provided by the expert. The method can elicit probabilities for a wide range of different event types, including new ways of eliciting probabilities for stochastically independent events and low‐probability events. We use a Monte Carlo simulation to test the accuracy of the approximated probabilities and try the method in practice, applying it to a real‐world risk analysis recently conducted for DEFRA (the U.K. Department for the Environment, Farming and Rural Affairs): the prioritization of animal health threats.