一类广义渐变磨损模型的可靠性分析

冲击模型在可靠性理论中扮演着很重要的角色,文章是在一类广义渐变磨损模型中引入冲击模型,得到系统的累计失效率函数,并以此来分析系统的可靠性,通过MATLAB实例分析了该模型在失效阀值和冲击量改变时系统的累积失效率的变化趋势。     

基于退化和随机冲击的非周期不完全预防维修模型

文章研究了存在两类故障的系统可靠度及非周期不完全预防维修模型.根据退化和随机冲击模型构建了系统的可靠度函数.为了满足可靠性要求,提出非周期不完全预防维修模型.以长期运行平均维修费用率最小为目标,给出不完全预防维修计划的确定方法,分析了模型参数对维修策略的影响.     

逐次定数截尾下Pareto分布的可靠性分析

基于逐次定数截尾模型,文章选取未知参数的先验分布为无信息先验分布,分别在平方损失和LINEX损失下,讨论了Pareto分布的形状参数,失效率以及可靠度函数的Bayes估计。最后运用Monte Carlo方法对Bayes估计和极大似然估计的MSE,进行了模拟比较。结果表明在LINEX损失下的Bayes估计更优。     

供求冲击与中国经济波动： 基于SVAR模型的甄别分析

 本文首先利用经全国经济普查信息修正后的季度数据推算得到1992年第1季度到2008年第3季度的实际GDP和GDP减缩指数,然后借鉴Blanchard和Quah（1989）提出的方法构建二元SVAR模型,对驱动中国经济波动的供求冲击进行甄别分析。结果发现：①无论是在长期还是在短期,2/3以上的产出波动可以归因于供给冲击的影响;②对于价格波动,短期内需求冲击和供给冲击的贡献几乎相当,而长期内需求冲击能够解释70％左右;③总的来说,供给冲击和需求冲击在中国经济波动中具有几乎同等的重要性。上述结论具有重要的宏观操作政策含义。     

中国股市动态VaR计量模型分析

风险测量是现代金融活动的中心。近年来,新兴的VaR测量方法已成为国际上风险管理的主流方法。文章介绍了利用GARCH模型的VaR计算方法,并比较了基于不同分布假设的4种GARCH模型计算的VaR值,并得出以下结论:证券市场收益率具有强烈的GARCH效应和非正态分布性;基于GARCH-T的VaR估计值在给定的显著性水平下能够有效地度量金融资产的风险。     

Weibull分布下基于MCMC的贝叶斯恒加试验数据评估

本文基于贝叶斯生存分析理论,在参数的有信息先验假设条件下,通过运用基于Gibbs抽样的马尔可夫链蒙特卡罗(MCMC)方法动态模拟出相关参数后验分布的马尔可夫链,给出恒加试验模型中各参数的贝叶斯估计;利用BUGS软件包对文献[6]中的实例进行建模分析,并将两种假设条件下MCMC具有显著差异的计算结果与传统BLUE结果进行比较,发现BLUE的计算结果近似等于将产品截尾数据当作失效数据时MCMC的处理结果;进而再次揭示出传统BLUE方法的不足,并证明了该模型在可靠性应用中的直观性与有效性。     

变环境条件下型号设备的可靠性估计

文章讨论了变环境条件下,Weibull寿命分布型号设备可靠性的估计问题:固定形状参数,在寿命特征参数为环境指标一元多项式情形下给出了可靠性估计方法;利用强大数律及控制收敛定理证明了估计量的强相合性,并通过大量仿真数据模拟说明了方法的可用性。     

基于GARCH模型的金融冲击对企业产出影响研究

利用GARCH模型,计算了来自货币供给、汇率以及股市波动因素的金融冲击,结果表明GARCH模型能够很好地反映金融冲击情况。根据GARCH模型分析结果,利用面板数据模型研究了金融冲击对企业产出的影响,实证研究显示:金融冲击会对企业产出有显著的影响,但单独股市波动的冲击对就业影响不显著;资产负债率高的企业,金融冲击会导致产出更大的下降。     

货币供给、出口和需求冲击对通胀的影响分析

文章在凯恩斯有效需求理论的基础上,构建了消费增长率、投资增长率、净出口增长率和货币供给增长率对通货膨胀的影响函数,并通过BSVAR模型的估计和预测,分析各个要素对通货膨胀率的冲击性影响.结果表明:消费冲击和投资冲击对通货膨胀的影响存在短期和长期效应,消费对通货膨胀的冲击要大于投资对通货膨胀的冲击;净出口当期在一定程度上也可以反作用于通货膨胀压力;货币政策滞后性和非政府性资金融通过大,在一定程度并没发挥货币政策短期作用.文章认为现阶段的通货膨胀主要来源于投资过热;合理规制金融机构的融资渠道发展可以增强货币政策的时效性.     

基于GARCH族模型的信息冲击对香港同业拆借市场的影响

香港同业拆借市场为香港商业银行和金融机构提供了短期资金借贷的平台。该市场形成的同业拆借利率HIBOR为存贷款利率的走向提供了重要参考。基于GARCH族模型研究了信息对香港同业拆借市场的冲击并绘制了相应的信息冲击曲线,发现PARCH-t(1,1)模型对数据的拟合度最高,发现信息对该市场的冲击具有明显的非对称性,好消息比坏消息给该市场带来的冲击更大。     

Business-Cycle Analysis With a Markov-Switching Model

This article explores the Hamilton Markov-switching model through an analysis of the business cycles of eight developed market economies. Forecasting and specification tests suggest only marginal improvements over linear autoregressive models. Yet filtered and smoothed conditional probabilities indicate turning points in business cycles that closely correlate with turning points from traditional methods. Tests regarding the asymmetry of business cycles reject the null of symmetry for most countries.     

Optimal Block Designs With Interference Effects From Neighboring Units Under a Non Additive Model

Here, the optimality of block design with interference effect from neighboring unit under a general non additive model is investigated, which allows for the presence of interactions among the treatments applied in the adjacent plots. A non additive model with interference × direct effects of treatments is considered as these effects contribute significantly to the response. A class of complete block designs balanced for interference effects from left neighboring unit is shown to be universally optimal for the estimation of direct and interference effects of treatments and two such series of designs have been constructed. Furthermore, considering direct treatment × block non additivity with interference effects, the optimality is studied and the optimal designs are obtained.     

离散选择模型在产品差别研究中的应用

The paper introduces to the application of three scatter choosing model to describe consumer's choice, thereby to conduct the demand analysis by using the consumers' materials and the cross section materials of market quotation.     

Extended Hazard Regression Model for Reliability and Survival Analysis

We propose an extended hazard regression model which allows the spread parameter to be dependent on covariates. This allows a broad class of models which includes the most common hazard models, such as the proportional hazards model, the accelerated failure time model and a proportional hazards/accelerated failure time hybrid model with constant spread parameter. Simulations based on sub-classes of this model suggest that maximum likelihood performs well even when only small or moderate-size data sets are available and the censoring pattern is heavy. The methodology provides a broad framework for analysis of reliability and survival data. Two numerical examples illustrate the results.     

A Multivariate GARCH Model Incorporating the Direct and Indirect Transmission of Shocks

Theoretical models of contagion and spillovers allow for asset-specific shocks that can be directly transmitted from one asset to another, as well as indirectly transmitted across uncorrelated assets through some intermediary mechanism. Standard multivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models, however, provide estimates of volatilities and correlations based only on the direct transmission of shocks across assets. As such, spillover effects via an intermediary asset or market are not considered. In this article, a multivariate GARCH model is constructed that provides estimates of volatilities and correlations based on both directly and indirectly transmitted shocks. The model is applied to exchange rate and equity returns data. The results suggest that if a spillover component is observed in the data, the spillover augmented models provide significantly different volatility estimates compared to standard multivariate GARCH models.     

Bayesian Analysis of a Queueing System with a Long-Tailed Arrival Process

Internet traffic data is characterized by some unusual statistical properties, in particular, the presence of heavy-tailed variables. A typical model for heavy-tailed distributions is the Pareto distribution although this is not adequate in many cases. In this article, we consider a mixture of two-parameter Pareto distributions as a model for heavy-tailed data and use a Bayesian approach based on the birth-death Markov chain Monte Carlo algorithm to fit this model. We estimate some measures of interest related to the queueing system k-Par/M/1 where k-Par denotes a mixture of k Pareto distributions. Heavy-tailed variables are difficult to model in such queueing systems because of the lack of a simple expression for the Laplace Transform (LT). We use a procedure based on recent LT approximating results for the Pareto/M/1 system. We illustrate our approach with both simulated and real data.     

Minimizing Upper Bound of Ruin Probability Under Discrete Risk Model with Markov Chain Interest Rate

This article focuses on minimal upper bound of ruin probability for a discrete time risk model with Markov chain interest rate and stochastic investment return. The interest rate of bond market is assumed to be a stationary Markov chain, and the return process of a stock market can be negative. This article presents two kinds of methods for minimizing the upper bound of ruin probability. One method relies on recursive equations for finite time ruin probabilities and inductive approach, the other one depends on martingale approach. Numerical examples show that the martingale approach is better than the inductive one.     

A Discrete Time Parametric Model for the Analysis of Failure Time Data

This paper introduces a parametric discrete failure time model which allows a variety of smooth hazard function shapes, including shapes which are not readily available with continuous failure time models. The model is easy to fit, and statistical inference is simple. Further, it is readily extended to allow for differences between subjects while retaining the ease of fit and simplicity of statistical inference. The performance of the discrete time analysis is demonstrated by application to several data sets.     

竞买者出价来到过程的数学模型及其应用研究

利用基于MatLab编写的计算程序,对从eBay网站收集的20个拍卖子类的竞买者出价数据进行了分析,发现网上拍卖中竞买者出价次数随拍卖进程呈现三阶段特征;竞买者出价速率具有时变性,可利用Shmueli等给出的三段速率函数表达式进行描述;三段出价速率函数的非齐次泊松过程很好地刻画了网上拍卖中竞买者出价来到过程的特征。