CSP方案的中止规则［R］

本文引入中止概率的概念，讨论适用于各类连续抽样方案的中止规则［Ｒ］的统计特性。结果表明，规则［Ｒ］的添加不改变方案原有的基本统计特性，而且全面优于另一类已被广泛采用的规则［Ｓ］．     

用于连续抽样方案的两类更优的中止规则

本文提出并讨论了适用于各类连续抽样方案的两参数中止规则 [N ,c]和 [R ,d]。作为应用 ,以MIL STD 12 35B中公布的CSP V方案为例 ,计算并给出了相应的中止参数 ,还将 [N ,c],[R ,d]与已有的两类规则 [S],[R]进行了特性比较。结果表明 ,[N ,c]和 [R ,d]均具有更优的统计特性     

CPS—1方案的中止概率曲线及其应用

本文结合国家标准ＧＢ８０５２－８７，利用中止概率曲线的概念，讨论了连续抽样方案ＣＳＰ－１的中止检查规则及其统计特性，并提出了确定最优中止参数的原则和方法。     

CSP-V方案的特性参数及中止规则[R]

本文计算并给出连续抽样方案ＣＳＰ－Ｖ的三类特性参数，与ＡＯＱＬ相应的ＰＬ值，与操作特性值０．１相应的极限质量水平ＬＱ值，以及与ＡＱＬ，ＬＱ相应的中止概率Ｐ１，Ｐ２等。还讨论了在ＣＳＰ－Ｖ方案中以中止规则［Ｒ］代替现行中止规则［Ｓ］的可能性。     

CSP—1方案的中止概率曲线及其应用

本文结合国家标准ＧＢ８０５２—８７［１］，利用中止概率曲线的概念，讨论了连续抽样方案ＣＳＰ—１的中止检查规则及其统计特性，并提出了确定最优中止参数的原则和方法     

连续抽样方案的中止检查规则

本文借助于转移概率流向图及马尔可夫链的方法，证明了将仅在全检期间检出不合格品时才可能中止检查的中止检查规则添加在适用于被提交产品总数为无穷的各类连续抽样方案中，将不改变这些方案原有的基本统计特性。     

带有中止检查规则（n－i）的CSP－1方案

本文引人转移概率母函数及幂级数等方法讨论带有中止规则（ｎ＊－ｉ）的连续抽样方案ＣＳＰ－１的中止概率Ｐ＊得到了Ｐ＊作为ＣＳＰ－１方案的度量的理论特性，证明了Ｄｏｄｇｅ型ＣＳＰ－１方案与带有中止规则（ｎ＊－ｉ）的ＣＳＰ－１方案具有相同的ＡＯＱ，ＡＦＩ，ＯＣ函数．文末还给出了一些数值结果．     

转移概率流图的概率理论基础与应用方法（Ⅵ）——中止规则对调整型抽样方案复

解顺强。转移概率流向图的概率理论基础与应用方法（Ⅵ）－中止规则对调整型抽样方案复合ＯＣ函数影响的进一步讨论。数理统计与管理。１９９８．１７（６）本文运用转移概率流向图及其粘接方法，证明了当检查始于加严抽样方案时，不带中止规则的调整型抽样方案与带中止规则的相应的调整型抽样方案，两者的复合ＯＣ函数相同。     

带有中止检查规划（n—i）的CSP—1方案

本文引人转移概率母函数及幂级数等方法讨论带有中止规划（ｎ－ｉ）的连续抽样方案ＣＳＰ－１的中止概率Ｐ，得到了Ｐ作为ＣＳＰ－１方案的度量的理论特性，证明了Ｄｏｄｇｅ型，ＣＳＰ－１方案与带有中止规划的ＣＳＰ－１方案具有相同的ＡＯＱ，ＡＦＩ，ＯＣ函数，文末还给出了一些数值结果。     

转移概率流图的概率理论基础与应用方法（Ⅴ）：中止规则对调整形抽样方案 …

本文运用转移概率流向图及其粘接方法，首次证明当检查始于正常抽样方案时，不带中止规则的调整型抽样方案与中止规则的相应的调整型抽样方案，两者的复合ＯＣ函数不相同，且前者小于后者。     

Numbers of Success-Runs of Specified Length Until Certain Stopping Time Rules and Generalized Binomial Distributions of Order k

A new distribution called a generalized binomial distribution of order k is defined and some properties are investigated. A class of enumeration schemes for success-runs of a specified length including non-overlapping and overlapping enumeration schemes is rigorously studied. For each nonnegative integer less than the specified length of the runs, an enumeration scheme called -overlapping way of counting is defined. Let k and be positive integers satisfying < k. Based on independent Bernoulli trials, it is shown that the number of (– 1)-overlapping occurrences of success-run of length k until the n-th overlapping occurrence of success-run of length follows the generalized binomial distribution of order (k–). In particular, the number of non-overlapping occurrences of success-run of length k until the n-th success follows the generalized binomial distribution of order (k– 1). The distribution remains unchanged essentially even if the underlying sequence is changed from the sequence of independent Bernoulli trials to a dependent sequence such as higher order Markov dependent trials. A practical example of the generalized binomial distribution of order k is also given.     

一类投资时点问题的最优停止模型及其等待时间

针对收益流与一次性投入沉淀成本均不确定的一类风险项目,为使其预期总的贴现净收益最大,提出了寻找项目最优投资时点的最优停止模型.这种方法不依赖于金融市场的完备性及市场无套利.借助于高切原理,通过求解一个自由边界问题,得到模型的候选解.运用最优停止理论证明了其的确为最优解,从而显式地给出了该类风险项目的最优投资时点.进一步,显式给出了到达最优时点的平均等待时间.     

带停时的奇异型随机控制问题在金融投资模型中的应用

以随机分析的知识和最优控制理论为基础,讨论了一类带停时的奇异型随机控制的折扣费用问题在金融投资模型中的应用,将该带停时的奇异型随机控制模型的受控状态过程和费用函数结构都推广到了最一般的形式,使该模型的应用范围更加广泛.通过讨论一组相应的变分不等式的解,分别对退化和非退化两种情况给出了此随机控制问题的最优策略,相应得出了投资模型中的最佳决策,并且证明了变分不等式的解即为最优费用函数.与以往不同的是,所得的相关结论应用到了金融投资模型中,从而解决了一类金融投资问题.     

概率最优停止问题

本文在时齐马氏序列中引入了概率最优停时和(ε,B)概率最优停时的概念,得到了其显式表达式,从而在某种程度上弥补了期望最优时的不足.同时,本文研究了两种停止问题的关系,指出期望最优停时也是概率最优停时的特例,并证明了集合首达时也是一种概率最优时,进一步给出了首达时为有限的等价条件.     

Stopping rules,permutation invariance and sufficiency principle

In the context of sequential (point as well as interval) estimation, a general formulation of permutation-invariant stopping rules is considered. These stopping rules lead to savings in the ASN at the cost of some elevation of the associated risk—a phenomenon which may be attributed to the violation of the sufficiency principle. For the (point and interval) sequential estimation of the mean of a normal distribution, it is shown that such permutation-invariant stopping rules may lead to a substantial saving in the ASN with only a small increase in the associated risk.Work partially supported by (i) Office of Naval Research, Contract Number N00014-85-K-0548, and (ii) Office of Naval Research, Contract Number N00014-83-K-0387.     

Optimal Stopping Time Formulation of Adaptive Image Filtering

This paper presents an approach to image filtering based on an optimal stopping time problem for the evolution equation describing the filtering kernel. This approach allows us to obtain easily an adaptivity of the filter with respect to the noise level. Well-posedness of the problem and convergence of fully discrete approximations are proved and numerical examples are presented and discussed. Accepted 25 October 2000. Online publication 9 April 2001.     

A Class of Stochastic Diferential Equations with the Time Average

Stochastic diferential equations with the time average have received increasing attentions in recent years since they can ofer better explanations for some fnancial models.Since the time average is involved in this class of stochastic diferential equations,in this paper,the linear growth condition and the Lipschitz condition are diferent from the classical conditions.Under the special linear growth condition and the special Lipschitz condition,this paper establishes the existence and uniqueness of the solution.By using the Lyapunov function,this paper also establishes the existence and uniqueness under the local Lipschitz condition and gives the p-th moment estimate.Finally,a scalar example is given to illustrate the applications of our results.     

The Valuation of American Options with Stochastic Stopping Time Constraints

Abstract

This paper concerns the pricing of American options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi et al., we transform the constrained into an unconstrained optimal stopping problem. The transformation replaces the original payoff by the value of a generalized barrier option. We also provide a Monte Carlo method to numerically calculate the option value for multidimensional Markov processes. We adapt the Longstaff–Schwartz algorithm to solve the stochastic Cauchy–Dirichlet problem related to the valuation problem of the barrier option along a set of simulated trajectories of the underlying Markov process.