基于同单调理论的IBNR准备金估计的随机界

在对IBNR准备金估计的随机模型存在的不足进行分析的基础上,对采用二阶段广义线性模型得到的各单元IBNR准备金估计和的分布问题进行讨论.在考虑折现因子的基础上,采用同单调理论,得到各单元准备金估计的和在凸序意义下的随机界,并通过一个实例对所述方法进行验证.

独立的无界随机变量和的概率不等式

研究了在概率空间 (Ω ,T ,P)上 ,独立的无界随机变量和尾部概率不等式 ,提出了一种用切割原始概率空间 (Ω ,T ,P)的新型方法去处理独立的无界随机变量和· 给出了独立的无界随机变量和的指数型概率不等式· 作为结果的应用 ,一些有趣的例子被给出· 这些例子表明

无界随机集关于条期望的收敛性及其应用

在一定条件下，本文给出了无界随机集序列关于条件期望的弱上极限Ｆａｔｏｕ引理，由此还得到了无界随机集序列在Ｋ—Ｍ收敛性意义下的控制收敛定理和单调收敛定理。最后将上述结果应用于被积函数的图收敛性和积分原函的收敛性。

一类无穷维随机三角级数的收敛性

在有限维随机三角多项式的界的估计及其收敛性的基础上,研究在一定条件下,一类无穷维随机三角多项式在连续函数空间中的收敛性.

STOCHASTIC BOUNDARY ELEMENT METHODS FOR 3D PROBLEMS WITH BODY FORCES AND ITS APPLICATION IN RELIABILITY OF TURBINE DISKS

The stochastic boundary element method(SBEM)is developed in this paper for 3D problems with body forces and reliability analysis of engineering structures.The integral equations of SBEM are established by the approach of partial derivation with respect to stochastic variables,considering the yield limit,rotation speeds and material density to be the fundamental stochastic variables.Through analyzing a numerical example and a turbo-disk of an aeroengine,the results show that the method developed is successful.

RESEARCH ON IMPERFECTION SENSITIVE REGION OF SINGLE-LAYER LATTICED DOMES

The concept of the imperfection sensitive region is given. The advanced stochastic imperfection method is used to research the imperfection sensitive region of single-layer latticed domes. Taking a K6 single-layer latticed dome with a diameter of 50 m as an example, its imperfection sensitive region is made up of the first 12 kinds of joints. The influence of the imperfections of support joints on the stability of the K6 single-layer latticed dome is negligible. Influences of the joint imperfections of the main rib and the secondary rib on the structural stability are similar. The initial deviations of these joints all greatly lower the critical load of the dome. Results show that the method can analyze the structural imperfection sensitive region quantitatively and accurately.

Optimizing the wavefield storage strategy in reflection-acoustic logging reverse-time migration

In this paper,wavefield storage optimization strategies are discussed with respect to reverse-time migration(RTM)imaging in reflection-acoustic logging,considering the problem of massive wavefield data storage in RTM itself.In doing so,two optimization methods are proposed and implemented to avoid wavefield storage.Firstly,the RTM based on the excitation-amplitude imaging condition uses the excitation time to judge the imaging time,and accordingly,we only need to store a small part of wavefield,such as the wavefield data of dozens of time points,the instances prove that they can even be imaged by only two time points.The traditional RTM usually needs to store the wavefield data of thousands of time points,compared with which the data storage can be reduced by tens or even thousands of times.Secondly,the RTM based on the random boundary uses the idea that the wavefield scatters rather than reflects in a random medium to reconstruct the wavefield source and thereby directly avoid storing the forward wavefield data.Numerical examples show that compared with other migration algorithms and the traditional RTM,both methods can effectively reduce wavefield data storage as well as improve data-processing efficiency while ensuring imaging accuracy,thereby providing the means for high-efficiency and highprecision imaging of fractures and caves by boreholes.

A comparative analysis of multi-output frontier models

Recently, there have been more debates on the methods of measuring efficiency. The main objective of this paper is to make a sensitivity analysis for different frontier models and compare the results obtained from the different methods of estimating multi-output frontier for a specific application. The methods include stochastic distance function frontier, stochastic ray frontier, and data envelopment analysis. The stochastic frontier regressions with and without the inefficiency effects model are also com-pared and tested. The results indicate that there are significant correlations between the results obtained from the alternative estimation methods.

Telemonitoring and hemodynamic monitoring to reduce hospitalization rates in heart failure： a systematic review and meta-analysis of randomized controlled trials and real-world studies

Background Heart failure is a significant problem leading to repeated hospitalizations. Telemonitoring and hemodynamic monitoring have demonstrated success in reducing hospitalization rates, but not all studies reported significant effects. The aim of this systematic review and meta-analysis is to examine the effectiveness of telemonitoring and wireless hemodynamic monitoring devices in reducing hospitalizations in heart failure. Methods ＆ Results PubMed and Cochrane Library were searched up to 1st May 2017 for articles that investigated the effects of telemonitoring or hemodynamic monitoring on hospitalization rates in heart failure. In 31,501 patients （mean age： 68 ± 12 years; 61% male; follow-up 11 ± 8 months）, telemonitoring reduced hospitalization rates with a HR of 0.73 （95% CI： 0.65-0.83; P 〈 0.0001） with significant heterogeneity （I2 = 94%）. These effects were observed in the short-term （≤ 6 months： HR = 0.77, 95% CI： 0.65-0.89; P 〈 0.01） and long-term （≥ 12 months： HR = 0.73, 95% CI： 0.62-0.87; P 〈 0.0001）. In 4831 patients （mean age 66 ± 18 years; 66% male; follow-up 13 ± 4 months）, wireless hemodynamic monitoring also reduced hospitalization rates with a HR of 0.60 （95% CI： 0.53-0.69; P 〈 0.001） with significant heterogeneity （I2 = 64%）.This reduction was observed both in the short-term （HR = 0.55, 95% CI： 0.45-0.68; P 〈 0.001; I2 = 72%） and long-term （HR = 0.64, 95% CI： 0.57-0.72; P 〈 0.001; I2 = 55%）. Conclusions Telemonitoring and hemodynamic monitoring reduce hospitalization in both short- and long-term in heart failure patients

RANDOMIZED PARALLEL B & B ALGORITHM BASED ON TRANSPUTER NETWORK

A new randomized parallel B & B algorithm is presented based on the similarity between heuristic search and statistics, and tested on a transputer network. The test result proves that the algorithm has a high speedup ratio, reliability, flexibility and fault tolerance.

Modeling of Large ELM Suppressions for High Confinement Plasma in D Ⅲ-D

The H-mode discharges with high edge pressure gradients are expected for the economic feasibility of future fusion reactors. However, the high edge pressure gradients easily produce ELM instability , which generally can expel large, heat and particle loading to the divertor targets. These ELMs limit the core plasma performance and reduce the lifetime of divertor target plates. The transports of heat and particles outward across plasma boundary are useful to control density and impurity profiles for achieving steady state, high performance plasmas. Consequently, any technique to eliminate or mitigate large fast ELM impulses must replace the transient heat and particle transports with another slow process. Such a technique is high priority for a burning plasma device such as ITER.

WentzeI-Freidlin Estimates for Jump Processes in Semi-Group Theory： Upper Bound

Large deviations estimates for Poisson processes estimate the logarithm of rare events associated to a Poisson process which has more and more jump which are smaller and smaller. In stochastic analysis, they are valid on the whole path space. Asoociated to this jump process is a Markov semi-group. We translate in semi group theory the proof of Wentzel-Freidlin for these estimates by translating in semi-group theory some basical tools of stochastic analysis as the exponential martingales of stochastic analysis. These Wentzel-Freidlin estimates （upper-bound） are only true for the semi-group.

A New Latent Class Stochastic Frontier Model for the Best Practices ofUSA＇s Corporate Governance

In this paper, the authors study the association between firms＇ specific characteristics and performances for a sample of 320 American firms using a governance efficiency index, calculated by the stochastic frontier analysis. The use of a latent class in the specification of the model, allowed detecting two groups of firms according to their specific characteristics： the firm size, the leverage, the dividend yield, and the return on equity （ROE）. The results of affectation equation show that the probability to be in the second group （the most efficient） is more important when the firm size, the dividend yield, and the ROE are high, while a high leverage level decreases the chance to be in the first group （the less efficient）.

Influence of Inhomogeneity on Critical Behavior of Earthquake Model on Random Graph

We consider the earthquake model on a random graph. A detailed analysis of the probability distribution of the size of the avalanches will be given. The model with different inhomogeneities is studied in order to compare the critical behavior of different systems. The results indicate that with the increase of the inhomogeneities, the avalanche exponents reduce, i.e., the different numbers of defects cause different critical behaviors of the system. This is virtually ascribed to the dynamical perturbation.

基于污染Gamma分布的聚合风险模型及其在风险分类中的应用

分析了污染Gamma分布及其性质,讨论了基于污染Gamma分布的聚合风险模型.对模型的概率特性和参数估计进行了分析,并对该模型在风险分类中的应用进行了讨论.为克服索赔总量的分布函数在计算上的困难,利用同单调性理论得到了随机凸序意义下索赔总量随机变量S的随机上界S^c,对S^c的分布函数及限额损失保费进行了讨论.通过一个例子对所述结论的有效性进行验证.

Existence of Solutions for Forward-Backward Stochastic Differential Equations with Jumps and Non-Lipschitzian Coefficients

This paper studies for ward-back ward differential equations with Poisson jumps and with stopping time as termination. Under some weak monotonicity conditions and for non-Lipschitzian coefficients, the existence and uniqueness of solutions are proved via a purely probabilistic approach, while a priori estimate is given. Here, we allow the forward equation to be degenerate.

Weighted moments for a supercritical branching process in a varying or random environment

Let W be the limit of the normalized population size of a supercritical branching process in a varying or random environment. By an elementary method, we find sufficient conditions under which W has finite weighted moments of the form EWpl(W), where p > 1, l 0 is a concave or slowly varying function.

IDENTIFYING INFLUENTIAL SPREADERS IN ARTIFICIAL COMPLEX NETWORKS

A long-term common belief in complex networks is that,the most connected nodes are the most efficient spreaders.However,recent investigations on real-world complex networks show that the most influential spreaders are those with the highest fc-shell values.It is well-known that,many real-world complex networks have scale free(SF),small world(SW) properties,therefore,identification of influential spreaders in general artificial SF,SW as well as random networks will be more appealing.This research finds that,for artificial ER and SW networks,degree is more reliable than fc-shell in predicting the outcome of spreading.However,for artificial SF networks,fc-shell is remarkably reliable than degree and betweeness,which indicate that the four recently investigated real-world networks[Kitsak M,Gallos L K,Havlin S,Liljeros F,Muchnik L,Stanley H E,Makse H A,Identification of influential spreaders in complex networks,Nat.Phys.,2010,6:888-893.]are more similar to scale free ones.Moreover,the investigations also indicate us an optimal dissemination strategy in networks with scale free property.That is,starting from moderate-degree-nodes will be ok and even more economical,since one can derive roughly similar outcome with starting from hubs.

Berry-Esseen bounds and Cramér type large deviations for eigenvalues of random matrices.

We establish Berry-Esseen bounds and Cramér type large deviations for the eigenvalues of Wigner Hermitian matrices in the bulk and at the edge cases. Similar results are also obtained for covariance matrices.

Markov selection and W-strong Feller for 3D stochastic primitive equations

This paper studies some analytical properties of weak solutions of 3D stochastic primitive equations with periodic boundary conditions. The martingale problem associated to this model is shown to have a family of solutions satisfying the Markov property, which is achieved by means of an abstract selection principle. The Markov property is crucial to extend the regularity of the transition semigroup from small times to arbitrary times. Thus, under a regular additive noise, every Markov solution is shown to have a property of continuous dependence on initial conditions, which follows from employing the weak-strong uniqueness principle and the Bismut-Elworthy-Li formula.