The limit theorems for random walk with state space ℝ in a space-time random environment

We consider a discrete time random environment. We state that when the random walk on real number space in a environment is i.i.d., under the law, the law of large numbers, iterated law and CLT of the process are correct space-time random marginal annealed Using a martingale approach, we also state an a.s. invariance principle for random walks in general random environment whose hypothesis requires a subdiffusive bound on the variance of the quenched mean, under an ergodic invariant measure for the environment chain.     

带形上随机环境中随机游动的内蕴分枝结构

揭示了带形上随机环境中随机游动的内蕴分枝结构一带移民的多物种分枝过程.利用内蕴分枝结构,可精确表达游动的首次击中时.给出了内蕴分枝结构的如下两个应用:(1)计算出首次击中时的均值,给出游动大数定律速度的显示表达,(2)得到从粒子角度看环境的马氏链不变测度的密度函数的显示表达,进而可用另一种"站在粒子看环境"的方法直接证明游动的大数定律.     

可列非齐次马氏链泛函的一类强大数定律

本文用分析方法研究可列非齐次马氏链的泛函的极限性质，得到了一类不同形式的强大数定律，在其中通常形式的强大数定律中的数学期望被条件期望所代替，关于独立随机变量序列的若干经典强大数定律是本文结果的推论．     

Limit Theorems for Inverse Process T_n of Hawkes Process

We consider linear Hawkes process N_t and its inverse process T_n. The limit theorems for N_t are well known and studied by many authors. In this paper, we study the limit theorems for T_n. In particular, we investigate the law of large numbers, the central limit theorem and the large deviation principle for T_n. The main tool of the proof is based on immigration-birth representation and the observations on the relation between N_t and T_n.     

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本文的目的是要研究Cayley树图上奇偶马氏链场的渐近均分割性\bd 首先我们给出Cayley树 图上奇偶马氏链场关于状态和状态序偶出现频率的强大数定律, 然后证明其具有a.e.收敛性 的渐近均分割性\bd     

双无限环境中马氏链的强大数定律

在随机环境中马氏链的研究领域 ,构造了一时齐的马氏双链 ,讨论了它的存在性及基本性质 ,最后利用马氏双链的性质 ,得到了双无限环境中马氏链的函数极限定律 ,并给出了该链的函数强大数定律成立的两个充分条件     

On Markov Chain Approximations to Semilinear Partial Differential Equations Driven by Poisson Measure Noise

We consider the stochastic model of water pollution, which mathematically can be written with a stochastic partial differential equation driven by Poisson measure noise. We use a stochastic particle Markov chain method to produce an implementable approximate solution. Our main result is the annealed law of large numbers establishing convergence in probability of our Markov chains to the solution of the stochastic reaction-diffusion equation while considering the Poisson source as a random medium for the Markov chains.     

Limit theorems for monotonic particle systems and sequential deposition

We prove spatial laws of large numbers and central limit theorems for the ultimate number of adsorbed particles in a large class of multidimensional random and cooperative sequential adsorption schemes on the lattice, and also for the Johnson–Mehl model of birth, linear growth and spatial exclusion in the continuum. The lattice result is also applicable to certain telecommunications networks. The proofs are based on a general law of large numbers and central limit theorem for sums of random variables determined by the restriction of a white noise process to large spatial regions.     

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We study a birth and death process $\{N_t\}_{t\ge0}$ in i.i.d. random environment, for which at each discontinuity, one particle might be born or at most $L$ particles might be dead. Along with investigating the existence and the recurrence criterion, we also study the law of large numbers of $\{N_t\}$. We show that the first passage time can be written as a functional of an $L$-type branching process in random environment and a sequence of independent and exponentially distributed random variables. Consequently, an explicit velocity of the law of large numbers can be given.     

一类平均算子Markov链的极限定理

该文给出了一类平均算子Ｍａｒｋｏｖ链,并证明了对此类算子Ｍａｒｋｏｖ链,其大数定理,中心极限定理及重对数定律成立。     

随机变量序列的大数定律及常返性定理

对一类有界独立或相依的随机变量序列|ξn|,获得了它的伯努利大数定律、波雷尔强大数定律及常返性定理.作为应用,得出了Loève专著[1]中的推广的伯努利大数定律、常返性定理,改进了[1]中的推广的波雷尔强大数定律.     

GI/G/1排队系统队长的强大数定律和中心极限定理

本文首先证明当服务强度小于1时,GI/G/1排队系统的队长是一个特殊的马尔可夫骨架过程——正常返的Doob骨架过程,然后运用马尔可夫骨架过程的强大数定律和中心极限定理等重要结果,给出了队长的累积过程的期望和方差,并给出了该累积过程满足强大数定律和中心极限定理的充分条件。     

一类马尔可夫骨架过程的强大数定律和中心极限定理

基于马尔可夫骨架过程极限分布的已有研究结果,本文运用波莱尔-康特立引理、更新理论、科尔莫哥洛夫的强大数定律以及独立同分布情形的中心极限定理等重要理论,分别给出了一类马尔可夫骨架过程对应的累积过程满足强大数定律和中心极限定理的充分条件.     

Limit theorems for reinforced random walks on certain trees

Consider a linearly edge-reinforced random walk defined on the b-ary tree, b≥70. We prove the strong law of large numbers for the distance of this process from the root. We give a sufficient condition for this strong law to hold for general edge-reinforced random walks and random walks in a random environment. We also provide a central limit theorem. Supported in part by a Purdue Research Foundation fellowship this work is part of the author's PhD thesis.     

Weakly interacting particle systems on inhomogeneous random graphs

We consider weakly interacting diffusions on time varying random graphs. The system consists of a large number of nodes in which the state of each node is governed by a diffusion process that is influenced by the neighboring nodes. The collection of neighbors of a given node changes dynamically over time and is determined through a time evolving random graph process. A law of large numbers and a propagation of chaos result is established for a multi-type population setting where at each instant the interaction between nodes is given by an inhomogeneous random graph which may change over time. This result covers the setting in which the edge probabilities between any two nodes are allowed to decay to 0 as the size of the system grows. A central limit theorem is established for the single-type population case under stronger conditions on the edge probability function.     

Relation between the rate of convergence of strong law of large numbers and the rate of concentration of Bayesian prior in game-theoretic probability

We study the behavior of the capital process of a continuous Bayesian mixture of fixed proportion betting strategies in the one-sided unbounded forecasting game in game-theoretic probability. We establish the relation between the rate of convergence of the strong law of large numbers in the self-normalized form and the rate of divergence to infinity of the prior density around the origin. In particular we present prior densities ensuring the validity of Erd?s–Feller–Kolmogorov–Petrowsky law of the iterated logarithm.     

A Law of Large Numbers for the Power Variation of Fractional Lévy Processes

We prove a law of large numbers for the power variation of an integrated fractional process in a pure jump model. This yields consistency of an estimator for the integrated volatility where we are no longer restricted to a Gaussian model.     

On One Sufficient Condition for the Validity of the Strong Law of Large Numbers for Martingales

We prove a theorem on the strong law of large numbers for martingales. The existence of higher moments is not assumed. From the theorem proved, we deduce numerous well-known results on the strong law of large numbers both for martingales and for sequences of sums of independent random variables.     

大数定律MATLB随机模拟的规律性

第二作者等用一个哲学公式及0.9规格化了收敛过程,从而形象化地解释了概率论与随机计算中的若干定理,使模拟的数值规律化.基于数学软件MATLB进行了大数定律的随机模拟,直观形象地展示了1/n∑_(i=1)~nX_i到数学期望μ的收敛过程,与第二作者等的哲学公式相吻合,从而有助于学生理解和掌握大数定律.     

Risk aggregation and stochastic claims reserving in disability insurance

We consider a large, homogeneous portfolio of life or disability annuity policies. The policies are assumed to be independent conditional on an external stochastic process representing the economic–demographic environment. Using a conditional law of large numbers, we establish the connection between claims reserving and risk aggregation for large portfolios. Further, we derive a partial differential equation for moments of present values. Moreover, we show how statistical multi-factor intensity models can be approximated by one-factor models, which allows for solving the PDEs very efficiently. Finally, we give a numerical example where moments of present values of disability annuities are computed using finite-difference methods and Monte Carlo simulations.