线性调控分枝过程

本文提出了线性调控分枝过程和在零点停止的线性调控分枝过程的数学模型,并讨论了它们的均值、方差函数和灭绝概率,从而推广了[1]、[3]和[4]有关结果。     

线性不对称损失时非正态分布过程均值优化

针对常见的两种非正态分布———梯形分布和三角分布，研究线性不对称质量损失时其过程均值的优化问题，建立了梯形分布在五种不同情况下线性不对称质量损失的数学模型，基于以上模型给出了线性不对称质量损失时梯形分布最优过程均值的确定方法；研究三角分布在四种不同情况下线性不对称质量损失的数学模型，并给出了线性不对称质量损失时三角分布最优过程均值的确定方法。最后，用实例验证本过程均值优化模型的有效性。实例表明，应用线性不对称损失函数，适当的改变过程均值，可以有效地降低产品的质量损失，通过调整工艺过程将获得最佳经济效益。     

误差为线性过程时回归模型的估计问题

对一类非线性回归模型及线性模型，在误差是一个弱平稳线性过程及适当的条件下，获得了估计量的r-阶平均相合性、完全相合性和渐近正态性。     

线性平稳过程的协方差和均值估计的大偏差结果

本文讨论了具有有界输入的线性平稳过程的参数估计的大偏差的上界和下界。     

解线性目标规划的《量化优先因子法》—基于LP过程的算法

本文提出一种解线性目标规划及整数线性目标规划的《量化优先因子法》,即把目标规划中表示优先等级的优先因子 pl( l=1 ,2 ,… ,L)用能从数量级上刻划优先因子 Pl Pl+ 1的本质特征的数来表示 ,进而用 SAS/OR软件包中解线性规划的 LP过程即可求解此线性目标规划 .通过实例给出算法与用 LP过程求解的程序 .     

生物种群在污染环境中的生灭过程

建立了生物种群在污染环境中的一个线性生灭过程模型.利用马尔可夫过程的理论和方法,得到生物种群数量变化的概率分布,最后讨论了各模型参数的变化对生物种群生存的影响.     

线性过程的强逼近和重对数律

本文讨论由独立同分布随机变量列产生的线性过程的泛函型重对数律和强逼近, 同时又给出由NA随机变量列产生的线性过程的重对数律.     

线性调控分枝过程的渐近增长

本文讨论了线性调控分枝过程的增殖速度和极限分布.由于GaltonWatson过程是它的特殊情况,故本文推广了[4]、[5]中的有关结果.     

线性过程的收敛速度

设X_t=sum from j=0 to ∞ c_jε_(t-j)是一个线性过程,当{ε_t}是一个局部广义高斯随机序列时,我们获得了X_t的重对数收敛速度。     

局部广义高斯序列与广义线性过程

本文对局部广义高斯序列得到了ｒ阶绝对矩的上界不等式，进而对由其生成的广义线性过程｛Ｘｎ｝给出了ａ．ｓ．收敛的充分条件。     

独立平稳随机环境中的P—S—D分枝过程

本文研究了独立同分布的随机环境中的Ｐ－Ｓ－Ｄ分枝过程,获得了有关过程的渐近性态以及灭 绝概率的一些结果．     

A note on the stationarity of a threshold first-order bilinear process

In the present note we study the threshold first-order bilinear model

X(t)=aX(t−1)+(b₁1_{X(t−1)<c}+b₂1_{X(t−1)c})X(t−1)e(t−1)+e(t), tεN

where {e(t), tεN} is a sequence of i.i.d. absolutely continuous random variables, X(0) is a given random variable and a, b₁, b₂ and c are real numbers. Under suitable conditions on the coefficients and lower semicontinuity of the densities of the noise sequence, we provide sufficient conditions for the existence of a stationary solution process to the present model and of its finite moments of order p.     

Finite non-homogeneous semi-Markov processes: Theoretical and computational aspects

This paper gives basic definitions and properties related to what we call the non-homogeneous semi-Markov processes with a finite number of states using the formalism of counting processes, i.e. with intensity functions. We show how it is possible to get generalized Polya processes as a very particular case. We also treat the computational aspect by discretisation and as an application, we develop a social security problem.     

随机环境中多物种分枝游动质点密度矩阵的极限分布

本文研究了随机环境中的多物种分枝游动于时刻k,位置x的质点密度矩阵序列{M~(k)(x)}k>1的极限分布。我们在证明了M~(k)(x),k>1,x∈Z是k个独立同分布的矩阵值随机元的乘积的基础上,主要证明了随机序列{logM_(ij)~(k)(x)}k>1依某种意义规范后是渐近正态的。     

A stochastic production planning model with a dynamic chance constraint

This paper deals with the optimal production planning for a single product over a finite horizon. The holding and production costs are assumed quadratic as in Holt, Modigliani, Muth and Simon (HMMS) [7] model. The cumulative demand is compound Poisson and a chance constraint is included to guarantee that the inventory level is positive with a probability of at least α at each time point. The resulting stochastic optimization problem is transformed into a deterministic optimal control problem with control variable and of the optimal solution is presented. The form of state variable inequality constraints. A discussion the optimal control (production rate) is obtained as follows: if there exists a time t₁ such that t₁?[O, T]where T is the end of the planning period, then (i) produce nothing until t₁ and (ii) produce at a rate equal to the expected demand plus a ‘correction factor’ between t₁ and T. If t₁ is found to be greater than T, then the optimal decision is to produce nothing and always meet the demand from the inventory.     

Modelling Credit Risk in the Jump Threshold Framework

ABSTRACT

The jump threshold framework for credit risk modelling developed by Garreau and Kercheval enjoys the advantages of both structural- and reduced-form models. In their article, the focus is on multidimensional default dependence, under the assumptions that stock prices follow an exponential Lévy process (i.i.d. log returns) and that interest rates and stock volatility are constant. Explicit formulas for default time distributions and basket credit default swap (CDS) prices are obtained when the default threshold is deterministic, but only in terms of expectations when the default threshold is stochastic. In this article, we restrict attention to the one-dimensional, single-name case in order to obtain explicit closed-form solutions for the default time distribution when the default threshold, interest rate and volatility are all stochastic. When the interest rate and volatility processes are affine diffusions and the stochastic default threshold is properly chosen, we provide explicit formulas for the default time distribution, prices of defaultable bonds and CDS premia. The main idea is to make use of the Duffie–Pan–Singleton method of evaluating expectations of exponential integrals of affine diffusions.