关于重尾分布间的控制关系及其应用

得到了能控制一切轻尾分布及一切轻度重尾分布的分布的等价条件,得到了能控制一切轻尾分布的分布的等价条件,讨论了分布与其相应的均衡分布之间的控制关系,并给出了上述控制关系在和的分布的封闭性等方面的应用.     

保费随机复合二项模型的Gerber-shiu折现罚金函数

考虑保费随机收取的复合二项模型.得到了其Gerber-shiu折现罚金函数满足的递推公式,瑕疵更新方程及其渐近解,并且通过构造一个相关的复合几何分布函数,得到了这个更新方程的解析解.相应的也得到了一些相关精算量的渐近表示和分布函数,如破产前瞬时盈余分布的渐近解,导致破产的索赔额的分布函数.     

相似理论和泥沙的垂直分布

本文利用相似性原理处理了二维渠道均匀定常挟沙水流,在湍流脉动速度和含沙量涨落值相似的条件下,我们得到了泥沙垂直于挟沙水流的流动方向的含沙量分布.这个含沙量分布和扩散理论得到的含沙量分布略有差别,而和重力理论得到的含沙量分布则差别较大.     

广义矩阵分布下多元回归模型的贝叶斯推断

考虑具有奇异矩阵椭球等高分布误差的多元线性回归模型的贝叶斯统计推断,在非信息先验下得到了系数矩阵关于Hausdorff测度的后验边缘分布和未来观察值的预测分布,并得到了一类特殊奇异矩阵椭球等高分布下误差协方差矩阵的后验边缘分布.对于具有奇异矩阵正态分布误差的多元线性回归模型,在广义正态-逆Wishart共轭先验下得到了类似的后验边缘分布和预测分布结果.在上述两种先验分布下,回归系数矩阵的后验边缘分布和预测分布是双奇异矩阵t分布,这种分布具有关于Hausdorff测度的精确密度.结果表明,在非信息先验下,回归系数矩阵的后验边缘分布和未来观察值的预测分布在奇异矩阵椭球等高分布类中具有稳健性.     

多源验前信息下先验分布的稳健融合方法

根据多种先验分布与似然函数尾部特性的比较,给出了多源验前信息下先验分布的稳健融合方法.讨论了由该方法得到的融合先验分布的后验稳健性问题.最后的数值例子表明,由该方法得到的融合先验分布具有较好的稳健性,进一步验证了该方法的有效性.     

非对称Marshall-Olkin Laplace分布及其在自回归模型中的应用

引入了一种新的概率分布类—–非对称Marshall-Olkin Laplace分布(AMOL),讨论了这一分布类的性质,得到了其几乎所有的数字特征.最后讨论了非对称Marshall-Olkin Laplace分布在自回归分析中的应用,得到了以AMOL为边际分布的自回归模型的一个充分必要条件.     

关于亚纯函数幅角分布的一个注记

本文研究了亚纯函数的幅角分布.利用亚纯函数的零点和极点的分布得到了Borel分布和增长级之间的联系.并可用来得到一些其它亚纯函数幅角分布的结果.     

灯笼图的可定向嵌入亏格分布

本文主要利用联树法研究了图的亏格多项式,得到了一类新图(灯笼图)的嵌入亏格分布.证明了灯笼图和偶梯图的亏格分布具有相同的递推关系,从而得到了灯笼图的嵌入亏格分布的精确解.     

Alpha Power伽马分布的性质与应用

本文通过增加一个额外的形状参数,扩展了伽马分布,称这种新分布为alpha power伽马分布.发现该分布具有相对灵活的危险率函数.研究了它的性质,包括s阶原点矩、矩母函数以及次序统计量分布的显式表达.得到了熵、平均剩余寿命以及平均等待时间的积分表达.讨论了该分布在完全样本下参数的极大似然估计,得到了参数的Fisher信息矩阵.进一步,研究了一般Ⅱ型逐次截尾样本下的参数估计.最后通过一个实际数据分析说明了提出分布的实用性.     

Pareto严格稳定分布在保险理赔中的应用

本文研究了Pareto严格稳定分布在保险中的应用.利用极大似然估计的方法得到了Pareto严格稳定分布,正态分布和Pareto分布的参数估计.根据信息准则,表明Pareto严格稳定分布能够较好地拟合保险数据.     

Distributional Form of Little's Law for FIFO Queues with Multiple Markovian Arrival Streams and Its Application to Queues with Vacations

This paper considers stationary queues with multiple arrival streams governed by an irreducible Markov chain. In a very general setting, we first show an invariance relationship between the time-average joint queue length distribution and the customer-average joint queue length distribution at departures. Based on this invariance relationship, we provide a distributional form of Little's law for FIFO queues with simple arrivals (i.e., the superposed arrival process has the orderliness property). Note that this law relates the time-average joint queue length distribution with the stationary sojourn time distributions of customers from respective arrival streams. As an application of the law, we consider two variants of FIFO queues with vacations, where the service time distribution of customers from each arrival stream is assumed to be general and service time distributions of customers may be different for different arrival streams. For each queue, the stationary waiting time distribution of customers from each arrival stream is first examined, and then applying the Little's law, we obtain an equation which the probability generating function of the joint queue length distribution satisfies. Further, based on this equation, we provide a way to construct a numerically feasible recursion to compute the joint queue length distribution.     

On positive definite quadratic forms in correlatedt variables

Summary In this paper we extend Ruben's [4] result for quadratic forms in normal variables. He represented the distribution function of the quadratic form in normal variables as an infinite mixture of chi-square distribution functions. In the central case, we show that the distribution function of a quadratic form int-variables can be represented as a mixture of beta distribution functions. In the noncentral case, the distribution function presented is an infinite series in beta distribution functions. An application to quadratic discrimination is given.     

T-IPH分布的若干性质及其在排队论中的应用

本文讨论T-IPH分布的一些重要性质,其中T-IPH表示可数状态离散时间吸收生灭链吸收时间的分布.对该分布,首先给出了其概率生成函数(PGF),在此基础上,进~步给出了计算分布概率分布律以及阶乘矩数值结果的迭代公式.另外,还讨论了T-IPH分布在排队论中的一个应用.     

Formula for the Laplace transform of the projection of a distribution on the positive semiaxis and some of its applications

We obtain a formula for the Laplace transform of the restriction of an arbitrary probability distribution on the positive semiaxis in the form of a Cauchy-type integral in infinite limits of the characteristic function of this distribution. Using this result and the estimates of the concentration function of the sum of independent random variables, we derive a representation for the Laplace transform of the restriction of the harmonic measure on the positive semiaxis. In conclusion, we present an estimate of the lower ladder height distribution for the case in which the distribution of the value of the jump in a random walk is normal.     

越库模式下的卷烟配送业务流程再造研究——以西安市卷烟配送中心为例

论文分析西安市卷烟配送现状及配送流程中存在的问题,以西安市卷烟配送东区为例构建卷烟配送的越库模式,通过业务流程再造构建越库模式下的卷烟配送业务流程;采用ASME评测法及作业成本法分析业务流程再造前后的配送时间和配送成本。研究结果表明,越库模式下卷烟配送业务流程的再造能够有效地整合供应链资源,提高卷烟配送效率,降低卷烟配送成本。     

On the Distribution of Sums of Independent Exponential Random Variables Via Wilks’ Integral Representation

In this note we consider an alternative approach to compute the distribution of the sum of independent exponential random variables. In particular, by considering the logarithmic relation between exponential and beta distribution functions and by considering the Wilks’ integral representation for the product of independent beta random variables, we provide a closed-form expression for the distribution of the sum of independent exponential random variables. The expression we obtain is simpler than the ones previously obtained in the literature.     

On the limiting spectral distribution of the covariance matrices of time-lagged processes

We consider two continuous-time Gaussian processes, one being partially correlated to a time-lagged version of the other. We first give the limiting spectral distribution for the covariance matrices of the increments of the processes when the span between two observations tends to zero. Then, we derive the limiting distribution of the eigenvalues of the sample covariance matrices. This result is obtained when the number of paths of the processes is asymptotically proportional to the number of observations for each single path. As an application, we use the second moment of this distribution together with auxiliary volatility and correlation estimates to construct an adaptive estimator of the time lag between the two processes. Finally, we provide an asymptotic theory for our estimation procedure.     

Take (smoothed) risks when you are young, not when you are old: How to get the best from your pension plan

Using stochastic modelling, we demonstrate that the best investmentstrategy for the accumulation phase of a defined contributionpension plan is one that limits the range of returns that arecredited to the plan member's account. In particular, we showthat with-profit accumulation programmes which make use of asmoothing fund to smooth out returns over time dominate unit-linkedaccumulation programmes. However, for the distribution phase,we show that it is hard in practice for an investment-linkeddistribution programme to beat the income and security providedby a standard annuity, although we again find that, by avoidingextremely poor outcomes, with-profit distribution programmesdominate unit-linked distribution programmes. Return smoothingby means of a smoothing fund is therefore a valuable featureof any long-term investment programme both during the accumulationand distribution phases.     

Nonasymptotic analysis of robust regression with modified Huber's loss

To achieve robustness against the outliers or heavy-tailed sampling distribution, we consider an Ivanov regularized empirical risk minimization scheme associated with a modified Huber's loss for nonparametric regression in reproducing kernel Hilbert space. By tuning the scaling and regularization parameters in accordance with the sample size, we develop nonasymptotic concentration results for such an adaptive estimator. Specifically, we establish the best convergence rates for prediction error when the conditional distribution satisfies a weak moment condition.     

基于最大最小蚂蚁系统的物流配送中心选址算法的研究

提出了一种基于信息素自适应调节的最大最小蚂蚁系统的多物流配送中心选址算法,利用改进的蚁群算法的路径寻优机制结合蚂蚁聚集尸体的行为模式,根据物流配送总成本最低的原则将各配送点与候选配送中心进行聚类,合理选择配送中心。将已有物流配送模型进行拓展,加入经营管理成本。分别利用基本蚁群聚类算法和改进的蚁群聚类算法对配送中心选址进行仿真,实验结果表明在解决大规模配送中心选址问题时,改进的算法在解的质量和收敛速度方面明显优于基本蚁群聚类算法。