变保费率复合Poisson-Geometric过程风险模型的Gerber-Shiu折现惩罚函数

本文研究了当保费率随时间变化时的复合Poisson-Geometric过程的风险模型.通过无穷小方法,得到了该模型的Gerber-Shiu折现惩罚函数所满足的更新方程.在此基础上,推导出破产概率,破产前瞬时盈余,以及破产时刻赤字分布满足的更新方程.特别地,当个体索赔服从指数分布时,通过求解微分方程,得到了该模型的破产概率的显式表达式和所满足的不等式.最后通过数值模拟和算例分析,提出了保险公司的赔付政策和保费政策对自身风险的影响.     

两险种广义Erlang（2）风险模型的破产概率

本文考虑一类具有两个独立险种的风险模型的破产概率,假设该模型的两个索赔计数过程是独立的两个广义Erlang(2)过程。利用微分分析和矩阵表示,得到破产概率满足的一个积分-微分方程组及其边界条件。在索赔计数过程是普通Erlang(2)过程的情形下,证明了广义Lundberg方程有且仅有三个正的实数根,由此并结合破产概率满足的积分-微分方程组,给出了破产概率的Laplace变换。     

常利率下有阈红利边界的Erlang(2)风险模型的罚金折现期望函数

为了精确地描述风险投资商实际的经营状况,本文将一般的Erlang(2)风险模型推广为常利率下有阈红利边界的Erlang(2)风险模型。首先利用全概率公式对风险过程进行分析,得到了模型的罚金折现期望函数所满足的积分-微分方程及积分方程,然后在不带利率时将积分方程简化为"第二类非其次Volterra积分方程",给出了罚金折现期望函数的确切表达式,最后给出了不带利率时模型的破产概率及破产前瞬时盈余和破产赤字的联合分布的表达式。     

带延迟索赔和随机收入的离散风险模型的Gerber-Shiu分析（英）

破产理论是保险数学中的重要问题，它可以为保险公司决策者提供一个非常有用的早期风险预警手段．本文研究了一个带潜在延迟索赔和随机保费收入的复合二项风险模型．利用矩母函数的技巧，得到了 Gerber-Shiu 期望折罚函数的递推公式．特别地，还得到了贴现因子为 1 的特殊情形下的 Gerber-Shiu 期望折罚函数的解析表达式．最后还得到了实际应用中的一些重要的破产特征量，包括破产概率，破产时赤字的密度函数，破产前盈余与破产时赤字的联合密度函数，以及导致破产的索赔密度函数等．     

一类马氏调制风险模型的破产概率

本文研究一类马氏调制风险模型的破产概率,在此模型中索赔到达间隔和索赔额都受一外在马氏过程的影响,保费收入则受该外在的马氏过程和公司的储备金水平的影响.本文不仅考虑了随机环境对保险公司的影响,而且考虑了保险公司为了吸引新的顾客,会根据储备金的水平来调整保费收入.因此所考虑的保险模型更加贴近现实,更加易于应用.通过向后微分讨论,根据外在过程的马氏性,严格推导出破产概率所满足的积分方程.进一步,通过拉普拉斯变换的方法,给出了积分方程的解.最后,给出一个例子来展示所得结果的可行性和有效性.     

常利率下的更新风险模型

讨论了常利率下的更新风险模型，证明了索赔时刻Tk的资产余额Uδ（Tk)(k≥0)构成一个齐次马尔科夫链，且给出其转移概率Q（x,B)。利用转移概率得到了风险问题中的几个重要的量和分布；破产概率，破产时余额分布以及破产前瞬间余额分布的级数展开式和积分主程。     

具有线性红利界限的破产理论

本文讨论了存存线性红利界限的带随机干扰的经典风险模型,给出了破产概率的一个上界,并证明了生存概率及红利付款的期望现值分别满足一个积分-微分方程。最后给出了索赔额服从指数分布时生存概率及红利付款的期望现值的确切表达式。     

带随机干扰更新风险模型破产概率的局部定理

为推广经典风险过程以研究各种风险引发的破产的可能性,本文研究了保险金融领域中一个更为现实的模型:带随机干扰的更新风险模型的破产概率的渐近估计的局部化形式。在相对安全负荷条件下,采用纯概率的方法,得出了当索赔额为重尾索赔时破产概率的局部渐近等价式,它与原更新风险模型相应的破产概率的局部渐近等价式一致,说明在重尾索赔下,Wiener过程对破产概率的影响可以忽略。     

两步保费率下的Erlang（2）风险过程

本文研究了两步保费率下Erlang(2)风险过程,给出了Gerber-Shiu折现罚函数的两个微积分方程及其解或更新方程.在索赔额为指数分布条件下得到了两个与破产相关的量并计算出了相应的数值结果.     

基于进入过程具有常利率和正则变化索赔的风险模型的渐近破产概率(英文)

本文研究了一类带常利率的,并且索赔过程由进入过程驱动的风险保险模型。在进入过程是一般更新过程以及索赔额是正则尾分布的条件下,得到了当初始资本趋于无穷时,破产概率的渐近行为,类似的结论对于进入过程是齐次泊松过程的情形也同样成立。     

Quantum Statistical Properties of Mixed Degenerate and Non-degenerate Parametric Processes

Abstract

Quadrature and integrated intensity fluctuations are found for mixed degenerate and non-degenerate optical parametric processes in single and compound modes. Additionally to quantum statistical effects for single processes new phenomena can occur arising from the coupling of both the processes, which can support squeezing of vacuum fluctuations and sub-Poisson photon statistics in single and compound modes.     

硫酸盐岩与碳酸盐岩复合岩溶发育机理与工程效应研究

硫酸盐岩和碳酸盐岩常共同分布,以往多是分别研究其岩溶发育。文章主要从自然条件上研究两者复合岩溶发育的机理,探讨了化学岩溶作用过程和生物岩溶作用的机理。复合岩溶中,陷落柱是很重要的一个特征。文章也探索了复合岩溶作用中,有关岩溶地下水的水质情况。     

Compound feature recognition by web grammar parsing

A method is presented to automatically recognize compound features using web grammar parsing on a solid model graph. A compound feature is a class of regional shapes with a variable topology. Examples of compound features are connected features, which contain a variable number of simple features connected together, and intersecting features, which intersect one another creating different shapes from the original simple features conceived. The simple features are regional shapes related to preestablished application processes. A solid object, stored as a boundary representation, is transformed to a web representation (a node-labeled graph) which is the input of a web parsing system for feature recognition. And a compound feature is described as a web grammar. From the web representation of an object shape, the compound feature recognition can be accomplished by parsing the web with the web grammar. The application of a web grammar enables a user to define a compound feature and makes feature recognition a formalized process for subsequent recognition.     

An economic design model for X¯ charts with random sampling policies

Recent literature contains many papers on the study of variable (but deterministic) sampling interval (VSI) policies for X¯ control charts. VSI policies perform better than their corresponding classical fixed-sampling-interval (FSI) policies. Results are also available in the literature for an adaptive VSI policy, an enhancement of the VSI policy, where the sample size also changes with the sampling interval. However, for many industrial (especially continuous) processes where X¯ charts are used, maintaining deterministic time intervals between samples is not possible owing to inherent randomness of the processes. In this paper we propose a new variable sampling policy, named random sampling policy (RSP), for X¯ charts in which the sampling intervals and the sample sizes (considered a function of the sampling intervals) are treated as random variables. An economic modeling framework for design of RSP with run rules is developed. Within the proposed modeling framework, special cases of RSP, such as VSI and FSI policies with and without run rules, can also be evaluated. An application of the economic model is demonstrated through design of RSP parameters for two numerical example problems.     

Exact two‐sided statistical tolerance limits for sample variances

Statistical tolerance intervals are widely used in the industry and in various areas of sciences, especially in conformity assessment and acceptance of products or processes in terms of quality. When the interest is in precision, a tolerance interval for the variance is useful. In this paper, we consider two‐sided tolerance intervals for the population of sample variances for data that arise from a normal distribution. These intervals are useful in applications where one needs information about process deterioration as well as process improvement, to properly assess product quality. In this paper, the theory for these tolerance intervals is developed and tables for the tolerance factors, required to calculate the proposed tolerance limits, are provided for various settings. Construction and implementation of the proposed tolerance intervals are illustrated using a dataset from a real application. Summary and conclusions are offered.     

渤海北部冰厚重现值的极大似然法区间估计

不同重现期的年极值冰厚是有冰海区建筑物设计的关键指标。目前在确定设计冰厚时,往往只给出点估计。而求解设计冰厚的置信区间,在某一置信水平下获取设计值的范围,可以确定设计重现值的不确定性,给海工结构物的设计与建造提供指导。采用极大似然方法区间估计,给出了Gumbel分布、三参数Weibull分布、三参数对数正态分布和P-III型分布置信区间的求解过程。利用渤海北部营口和葫芦岛海区历年总冰厚极大值的实测数据,基于以上4种分布型式,采用极大似然法求得不同重现期下冰厚重现值的置信区间,并对各分布型式进行了优选比较。结果表明,选取P-III型分布求解这两地海冰厚度重现值的置信区间较优。     

Application of a microbial toxicity assay for monitoring treatment effectiveness of pentachlorophenol in water using UV photolysis and TiO2 photocatalysis

Conventional approaches for monitoring the effectiveness of wastewater treatment processes include evaluating the degradation of the target compound and/or generation of its nontoxic byproducts. These approaches are, however, limited because routine chemical analyses alone are neither able to fully address potential hazard to biological receptors nor characterize potential synergistic interactions. This study was carried out to investigate the degradation effectiveness of pentachlorophenol (PCP) by treatment with UV-A, UV-B photolysis, sunlight, TiO(2) photocatalysis, and/or their combinations. Chemical analyses of the parent compound and its selected byproducts, as well as acute toxicity assessment using the luminescent bacteria Vibrio fischeri (Microtox), were conducted during and after the various photolytic and photocatalytic treatments. In general, the toxicity reduction pattern observed after treatment corresponded well with the chemical degradation data. However, it should be noted that there were occasions that acute microbial toxicity was observed even from the treated water samples, some of which showed complete removal of the parent compound. This post-treatment toxicity might be due to toxic PCP byproducts, which may include polychlorinated dibenzodioxins/furans, tetrachloro-p-benzoquinone, and other intermediates. The TiO(2) photocatalysis with UV-B photolysis was the most effective method to remove both PCP and its toxic derivatives in the water. The Microtox assay is an easy to use and promising approach for evaluating the effectiveness of wastewater treatment processes.     

Principles and applications of broadband acoustic resonance dissolution spectroscopy (BARDS): a sound approach for the analysis of compounds

The dissolution of a compound results in the introduction and generation of gas bubbles in the solvent. This formation is due to entrained gases adhered to or trapped within the particles. Furthermore, a reduction in gas solubility due to the solute results in additional bubble generation. Their presence increases the compressibility of the solvent with the added effect of reducing the velocity of sound in the solvent. This effect is monitored via the frequency change of acoustic resonances that are mechanically provoked in the solvent and are now used as an insightful analytical technique. An experimental set up was designed to study a large number of compounds as a function of time, concentration, and solvent system. This revealed the role of the various physical and chemical mechanisms in determining the observed response. It is also shown that this response is strongly dependent on the physical and chemical characteristics of the solute compound used, therefore resulting in a method for the characterization of compounds and mixtures. Additional factors such as morphology (polymorphism), particle size, and dissolution rate are shown to be key in the variation of the resulting response. A mathematical model has also been developed in parallel, which inter-relates the various processes involved in the observed response. It is anticipated that BARDS will open up a new window into transient dissolution processes and compound characterization.     

Multivariate process incapability vector

Process capability indices evaluate the capability of the processes in satisfying customer's requirements. This paper introduces a superstructure multivariate process incapability vector for multivariate normal processes and then, compares it with four recently proposed multivariate process capability indices to show its better performance. In addition, the effects of two modification factors are investigated. Also, bootstrap confidence intervals for the first component of the proposed vector are obtained. Furthermore, real manufacturing data sets are presented to demonstrate the applicability of the proposed vector.