响应变量随机缺失下的半参变系数模型的均值估计

在响应变量随机缺失时,研究了半参数变系数模型响应变量均值的借补估计.首先利用完整个体估计模型中的参数与非参数部分,然后再用借补方法与加权借补方法估计响应变量的均值.最后求出了估计的渐近偏差与渐近方差,研究了所得到的估计的渐近性质,并进行模拟比较.     

带有无限到达源的Re-entrant Line的稳定性

用Foster判别准则,Weiss[13]给出了带有无限到达源的两站三步re-entrant line的稳定性的充分条件．本文用两种不同的方法得到了其稳定性的充分必要条件,即: 二维随机游动方法和Foster判别准则．同时,我们又用流体模型方法得到了系统稳定的充分条件,大大地简化了Weiss[13]的证明．     

Concentration for self‐bounding functions and an inequality of Talagrand

We see that the entropy method yields strong concentration results for general self‐bounding functions of independent random variables. These give an improvement of a concentration result of Talagrand much used in discrete mathematics. © 2006 Wiley Periodicals, Inc. Random Struct. Alg., 2006     

随机动力系统的进展和问题

本文主要介绍随机动力系统的主要成果和进一步研究的问题。     

对模糊随机向量凸集的定义及探讨

在模糊随机变量的基础上引入了模糊随机向量凸集的概念,给出了几个模糊随机凸集的例子.     

Moderate and Small Deviations for the Ranges of One-Dimensional Random Walks

We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm. We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm.     

Learning Markov chains in fractal compression of image data

In a recent paper [17] we proposed a stochastic algorithm which generates optimal probabilities for the decompression of an image represented by the fixed point of an IFS system (SAOP). We show here that such an algorithm is in fact a non trivial example of Generalized Random System with Complete Connections. We also exhibit a generalization which could represent the solution to the inverse problem for an image with grey levels, if a fixed set of contraction maps is available. Received: 1 July 2002     

一类随机环境中的随机游动

在Solomn的模型的基础上对一类随机环境中随机游动进行了讨论，并得出了一个常返性准则和一些极限性质。     

Some Invariance Principles for Random Vectors in the Generalized Domain of Attraction of the Multivariate Normal Law

For independent identically distributed random vectors belonging to the generalized Domain of Attraction of the multivariate normal law, we define two partial sum processes analogous to that of Donsker's Theorem. We prove that each converges in distribution to a Brownian Motion in the space of continuous functions. One process uses nonrandom operator normalization, and the other is a studentization of the first, using normalization by the empirical covariance operator.     

密度演化方法在求解股市上扬天数中的应用

将股市上扬的天数转化为随机游程的长度，利用密度演化方法求得了股市上扬天数的分布以及均值和方差该文首次将密度演化方法用来研究股市的一般宏观规律，其结论可指导投资决策．