Archimedean copula刻画的尺度比例失效率模型的极小次序统计量的随机序北大核心CSCD

在多元链式优化序下,该文研究了两组来自于不同相依尺度比例失效率分布的最小次序统计量的随机比较.在某种数学意义下,一个由尺度比例失效率分布的不同脆弱参数和尺度参数构成的矩阵变化到另一个矩阵时,该文研究了在一定的条件下,来自于第一个尺度比例失效率分布的最小次序统计量在普通随机序下小于变化到的参数矩阵对应的尺度比例失效率分布的最小次序统计量.该文也给出了一些数值例子来说明得到的结果的正确性.     

Gompertz分布顺序统计量的一些随机比较

考虑两组相互独立的来自非齐次总体Gompertz分布的样本,给出了最小顺序统计量的反向失效率序、散度序以及凸变换序之间的比较和最大顺序统计量的普通随机序的比较.     

逆Weibull分布随机变量的随机比较(英文)

研究了两个相互独立的逆Weibull分布随机变量间的随机序,似然比序,危险率序以及凸序之间的相互关系,给出了两个相互独立但不同分布的随机变量满足各种随机序时其分布所含参数间的相应关系.也给出了两组相互独立但不同分布的随机变量极值间在一般随机序下的大小关系.     

逆Weibull分布随机变量的随机比较

研究了两个相互独立的逆Weibull分布随机变量间的随机序,似然比序,危险率序以及凸序之间的相互关系,给出了两个相互独立但不同分布的随机变量满足各种随机序时其分布所含参数间的相应关系．也给出了两组相互独立但不同分布的随机变量极值间在一般随机序下的大小关系．     

Ⅰ型极值分布随机变量的随机比较

研究了两个相互独立的Ⅰ型极大值分布随机变量间的随机序,似然比序,危险率序及凸序之间的相互关系,给出了两个相互独立但不同分布的随机变量满足各种随机序时其分布所含参数间的相应关系．文中也给出了两组相互独立但不同分布的随机变量极值间在一般随机序下的大小关系．     

Ⅰ型极值分布随机变量的随机比较(英文)

研究了两个相互独立的Ⅰ型极大值分布随机变量间的随机序,似然比序,危险率序及凸序之间的相互关系,给出了两个相互独立但不同分布的随机变量满足各种随机序时其分布所含参数间的相应关系.文中也给出了两组相互独立但不同分布的随机变量极值间在一般随机序下的大小关系.     

广义次序统计量间隔的多维随机排序

本文研究了附加于广义次序统计量底分布以及参数的条件, 使得人们在多维似然比序和多维通常随机序意义下对广义次序统计量的间隔向量进行比较, 同时也给出了文中主要结果的应用.     

相依结构样本次序统计量的随机比较及逐步删失寿命试验参数估计方法研究

对一组已知寿命分布的样本开展寿命试验,失效时刻构成一组次序统计量。本文研究带有相依结构的齐次和非齐次样本的次序统计量在通常随机序意义下的比较方法,将Ma (1997)针对独立样本的结果推广到相依样本的情形,并将推广后的结果应用到可靠性寿命试验中逐步删失次序统计量的随机比较中。最后,结合一个产品逐步删失寿命试验的案例,研究如何基于试验数据,对产品的寿命分布参数进行估计,进而研究了参数估计效果与哪些因素有关。     

多项分布总体的相等对增凸序问题的多样本检验

概率分布间随机序在实践中已经得到了广泛的应用,而且似然比检验是用以检验涉及随机序问题的最普遍的检验方法．但是,关于多个多项式总体间的增凸序约束的统计推断问题并没有得到充分发展．多样本的增凸序对无约束的检验问题已被研究．然而,多总体的相等性对增凸序的假设检验问题似乎更有研究意义．并且分布的相等对随机序的假设检验问题往往是统计学家最为普遍地考虑．对多样本的情况,本文考虑了分布的相等对增凸序的假设检验问题,并且获得似然比检验统计量的零渐近分布,它是一组x~2分布随机变量的加权和,即■~2分布．     

半参数回归模型中随机加权M估计的强逼近

用随机加权法给出了半参数回归模型中参数的随机加权M估计，在一般的条件下证明了用随机加权统计量的分布逼近原估计量误差的分布的强有效性，并给出了M估计的最优强收敛速度。     

On Stochastic Orders for Sums of Independent Random Variables

In this paper, it is shown that a convolution of uniform distributions (a) is more dispersed and (b) has a smaller hazard rate when the scale parameters of the uniform distributions are more dispersed in the sense of majorization. It is also shown that a convolution of gamma distributions with a common shape parameter greater than 1 is larger in (a) likelihood ratio order and (b) dispersive order when the scale parameters are more dispersed in the sense of majorization.     

Some new results on convolutions of heterogeneous gamma random variables

Convolutions of independent random variables often arise in a natural way in many applied areas. In this paper, we study various stochastic orderings of convolutions of heterogeneous gamma random variables in terms of the majorization order [p-larger order, reciprocal majorization order] of parameter vectors and the likelihood ratio order [dispersive order, hazard rate order, star order, right spread order, mean residual life order] between convolutions of two heterogeneous gamma sets of variables wherein they have both differing scale parameters and differing shape parameters. The results established in this paper strengthen and generalize those known in the literature.     

Comparisons on aggregate risks from two sets of heterogeneous portfolios

In this paper, we stochastically compare the aggregate risks from two heterogeneous portfolios. It is shown that under suitable conditions the more heterogeneities among aggregate risks would result in larger aggregate risks in the sense of the stochastic order. The stochastic properties of aggregate risks when the claims follow proportional hazard rates models or scale models are studied. We also provide sufficient conditions for comparing the aggregate risks arising from two sets of heterogeneous portfolios with claims having gamma distributions. In particular, the aggregate risks of portfolios from dependent samples with comonotonic dependence structures or arrangement increasing density functions are discussed. The new results established strengthen and generalize several results known in the literature including Ma (2000), Khaledi and Ahmadi (2008), Xu and Hu (2011), Xu and Balakrishnan (2011), Pan et al. (2013) and Barmalzan et al. (2015).     

Stochastic comparisons of series and parallel systems with generalized linear failure rate components

In this paper, we discuss stochastic comparisons of series and parallel systems comprising independent and heterogeneous generalized linear failure rate components. When a system with possibly different shape and scale parameters has its matrix of parameters changing to another matrix of parameters in a certain mathematical sense, we examine the usual stochastic order of the smallest and largest order statistics under such a setup. Copyright © 2017 John Wiley & Sons, Ltd.     

Mean residual life order of convolutions of heterogeneous exponential random variables

In this paper, we study convolutions of heterogeneous exponential random variables with respect to the mean residual life order. By introducing a new partial order (reciprocal majorization order), we prove that this order between two parameter vectors implies the mean residual life order between convolutions of two heterogeneous exponential samples. For the 2-dimensional case, it is shown that there exists a stronger equivalence. We discuss, in particular, the case when one convolution involves identically distributed variables, and show in this case that the mean residual life order is actually associated with the harmonic mean of parameters. Finally, we derive the “best gamma bounds” for the mean residual life function of any convolution of exponential distributions under this framework.     

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In this paper, we study the stochastic comparisons of order statistics from generalized normal distributions. We obtain some sufficient conditions for ordering results based on parameter matrix and vector majorization comparisons. These conditions are necessary in some cases.     

不确定性对混合CVaR约束库存系统的影响

运用应用概率中的随机占优研究需求不确定性对混合CVaR约束库存系统最优订购量和最优利润的影响。引入刻画决策者风险态度的“风险偏好系数”,得到系统最优订购量和最优利润关于风险偏好系数的单调性。研究表明随机大需求总会导致系统较高的最优订购量和最优利润;在割准则序意义下,最优订购量可能随需求可变性的增加而增加也可能随需求可变性的增加而减少;在二阶随机占优且风险偏好系数大于等于1的情况下系统最优利润具有随机单调性,然而当风险偏好系数小于1时最优利润在二阶随机占优意义下的结论不一定成立,我们通过一个数值例子来说明。     

Fast and Accurate Approximation of the Full Conditional for Gamma Shape Parameters

The gamma distribution arises frequently in Bayesian models, but there is not an easy-to-use conjugate prior for the shape parameter of a gamma. This inconvenience is usually dealt with by using either Metropolis–Hastings moves, rejection sampling methods, or numerical integration. However, in models with a large number of shape parameters, these existing methods are slower or more complicated than one would like, making them burdensome in practice. It turns out that the full conditional distribution of the gamma shape parameter is well approximated by a gamma distribution, even for small sample sizes, when the prior on the shape parameter is also a gamma distribution. This article introduces a quick and easy algorithm for finding a gamma distribution that approximates the full conditional distribution of the shape parameter. We empirically demonstrate the speed and accuracy of the approximation across a wide range of conditions. If exactness is required, the approximation can be used as a proposal distribution for Metropolis–Hastings. Supplementary material for this article is available online.     

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??In this paper, we compare the smallest order statistics arising from multiple-outlier models when the numbers of independent and identically distributed random variables are different. Let and denote the smallest order statistics among, and, respectively, whereand. We then prove that $ and are ordered in terms of the usual stochastic order, hazard rate order and likelihood ratio order under the majorization relationship between and.     

同单调相依结构下两重生命模型的概率分布

在寿险实务中,在处理涉及到多个生命的问题时往往假设各个生命之间是独立的,但事实上,因为受某些相同因素影响的生命之间总是存在一定的正相依性．本文证明了在给定边际分布的二维随机向量中,同单调相依结构是在相关序意义下最强的正相依结构,研究了在此相依结构下的两重生命模型的概率分布,并给出了随机序意义下两个状态消亡时间的随机上界和随机下界．