On the First Exit Time of a Completely Asymmetric Stable Process from a Finite Interval

We compute the Laplace transform of the distribution of thefirst exit time from a finite interval for a completely asymmetricstable process. The formula involves a Mittag-Leffler functionand its derivative. As an application, we determine the asymptotictail behaviour of the foregoing distribution, and deduce anextension of the law of the iterated logarithm of Chung.     

具有不良影响的一类存贮过程的首中时

考虑一类具有正负跳(正负跳大小服从Erlang分布)的存贮过程的首中时,利用马氏无穷小算子的方法来刻画首中时的拉普拉斯变换.     

First Passage Time Distribution for Linear Functions of a Random Walk

In this paper, theorems about asymptotic behavior of the local probabilities of crossing the linear boundaries by a perturbed random walk are proved.     

允许赤字的MAP风险过程首达时

保险公司作为负债经营的特殊企业,其偿付能力受到监管部门的约束,本文以公司负债经营为前提研究其各种首次时.考虑MAP风险过程,即存在一随机背景Markov过程,索赔到达与索赔大小同时受这一背景过程影响,索赔到达为Markov到达点过程(MAP),索赔大小对于不同的背景状态具有不同的分布.本文给出首达时满足的积分-微分方程,通过求解带边界条件的积分-微分方程,给出了盈余过程从初始盈余水平到达某一给定盈余水平的首达时的Laplace变换的矩阵表示式,并由此推得了盈余过程到达指定水平的若干首达事件概率.     

Exponentiality of First Passage Times of Continuous Time Markov Chains

Let \((X,\mathbb{P}_{x})\) be a continuous time Markov chain with finite or countable state space S and let T be its first passage time in a subset D of S. It is well known that if μ is a quasi-stationary distribution relative to T, then this time is exponentially distributed under  \(\mathbb {P}_{\mu}\) . However, quasi-stationarity is not a necessary condition. In this paper, we determine more general conditions on an initial distribution μ for T to be exponentially distributed under  \(\mathbb{P}_{\mu}\) . We show in addition how quasi-stationary distributions can be expressed in terms of any initial law which makes the distribution of T exponential. We also study two examples in branching processes where exponentiality does imply quasi-stationarity.     

Poisson Broken Lines Process and its Application to Bernoulli First Passage Percolation

In this note we introduce a process, which we call 'the Poisson broken lines process", and we compute the intensity of a point process which is obtained by intersecting the Poisson broken lines process with an abscissa axis. In the second part we apply this result to compute an explicit lower bound for the time constant of a planar Bernoulli first passage percolation model with the parameter p < p_c.     

The Passage Time Distribution for a Birth-and-Death Chain: Strong Stationary Duality Gives a First Stochastic Proof

A well-known theorem usually attributed to Keilson states that, for an irreducible continuous-time birth-and-death chain on the nonnegative integers and any d, the passage time from state 0 to state d is distributed as a sum of d independent exponential random variables. Until now, no probabilistic proof of the theorem has been known. In this paper we use the theory of strong stationary duality to give a stochastic proof of a similar result for discrete-time birth-and-death chains and geometric random variables, and the continuous-time result (which can also be given a direct stochastic proof) then follows immediately. In both cases we link the parameters of the distributions to eigenvalue information about the chain. We also discuss how the continuous-time result leads to a proof of the Ray–Knight theorem. Intimately related to the passage-time theorem is a theorem of Fill that any fastest strong stationary time T for an ergodic birth-and-death chain on {0,…,d} in continuous time with generator G, started in state 0, is distributed as a sum of d independent exponential random variables whose rate parameters are the nonzero eigenvalues of −G. Our approach yields the first (sample-path) construction of such a T for which individual such exponentials summing to T can be explicitly identified. Research of J.A. Fill was supported by NSF grant DMS–0406104 and by The Johns Hopkins University’s Acheson J. Duncan Fund for the Advancement of Research in Statistics.     

First Passage Time for Brownian Motion and Piecewise Linear Boundaries

We propose a new approach to calculating the first passage time densities for Brownian motion crossing piecewise linear boundaries which can be discontinuous. Using this approach we obtain explicit formulas for the first passage densities and show that they are continuously differentiable except at the break points of the boundaries. Furthermore, these formulas can be used to approximate the first passage time distributions for general nonlinear boundaries. The numerical computation can be easily done by using the Monte Carlo integration, which is straightforward to implement. Some numerical examples are presented for illustration. This approach can be further extended to compute two-sided boundary crossing distributions.     

Ultrametric Diffusion,Exponential Landscapes,and the First Passage Time Problem

In this article we study certain ultradiffusion equations connected with energy landscapes of exponential type. These equations are connected with the \(p\)-adic models of complex systems introduced by Avetisov et al. We show that the fundamental solutions of these equations are transition density functions of Lévy processes with state space \(\mathbb{Q}_{p}^{n}\), we also study some aspects of these processes including the first passage time problem.     

Moments of Absorption Time for a Conditioned Random Walk

A random walk on the set of integers {0,1,2,...,a} with absorbing barriers at 0 and a is considered. The transition times from the integers z (0<z<a) are random variables with finite moments. The nth moment of the time to absorption at a, D_z,n, conditioned on the walk starting at z and being absorbed at a, is discussed, and a difference equation with boundary values and initial values for D_z,n is given. It is solved in several special cases. The problem is motivated by questions from biology about tumor growth and multigene evolution which are discussed.     

On the First Hitting Time of a One-dimensional Diffusion and a Compound Poisson Process

It is studied the first-passage time (FPT) of a time homogeneous one-dimensional diffusion, driven by the stochastic differential equation dX(t) = μ(X(t))dt + σ(X(t)) dB _t , X(0) = x ₀, through b + Y(t), where b > x ₀ and Y(t) is a compound Poisson process with rate λ > 0 starting at 0, which is independent of the Brownian motion B _t . In particular, the FPT density is investigated, generalizing a previous result, already known in the case when X(t) = μt + B _t , for which the FPT density is the solution of a certain integral equation. A numerical method is shown to calculate approximately the FPT density; some examples and numerical results are also reported.     

Transient and First Passage Time Distributions of First- and Second-order Multi-regime Markov Fluid Queues via ME-fication

We propose a numerical method to obtain the transient and first passage time distributions of first- and second-order Multi-Regime Markov Fluid Queues (MRMFQ). The method relies on the observation that these transient measures can be computed via the stationary analysis of an auxiliary MRMFQ. This auxiliary MRMFQ is constructed from the original one, using sample path arguments, and has a larger cardinality stemming from the need to keep track of time. The conventional method to approximately model the deterministic time horizon is Erlangization. As an alternative, we propose the so-called ME-fication technique, in which a Concentrated Matrix Exponential (CME) distribution replaces the Erlang distribution for approximating deterministic time horizons. ME-fication results in much lower state-space dimensionalities for the auxiliary MRMFQ than would be with Erlangization. Numerical results are presented to validate the effectiveness of ME-fication along with the proposed numerical method.

     

On the Asymptotic Behavior of First Passage Time Densities for Stationary Gaussian Processes and Varying Boundaries

Making use of a Rice-like series expansion, for a class of stationary Gaussian processes the asymptotic behavior of the first passage time probability density function through certain time-varying boundaries, including periodic boundaries, is determined. Sufficient conditions are then given such that the density asymptotically exhibits an exponential behavior when the boundary is either asymptotically constant or asymptotically periodic.     

Directionally Convex Comparison of Correlated First Passage Times

Many important classes of multivariate distributions arising from reliability modeling are the distributions of correlated first passage times of certain multivariate point processes. In this paper, we obtain results that compare variability and dependence structure of these correlated first passage times, in the sense of directionally convex ordering. Under certain conditions, we also obtain some easily computable distributional bounds for the first passage times whose joint distributions can not be expressed explicitly.     

Some Explicit Results on First Exit Times for a Jump Diffusion Process Involving Semimartingale Local Time

Journal of Theoretical Probability - In this paper, we consider the one-sided and the two-sided first exit problem for a jump diffusion process with semimartingale local time. Denote this process...     

Exit Times,Overshoot and Undershoot for a Surplus Process in the Presence of an Upper Barrier

We study the movement of a surplus process with initial capital u in the presence of two barriers: a lower barrier at zero and an upper barrier at b (b > u). More specifically, we consider the behaviour of the surplus: (a) in continuous time; and (b) only at claim arrival times. For each of these cases, we find the expected time until the process exits the interval [0,b]. We also obtain results related to the undershoot and overshoot of the surplus which, in particular for case (b) above, are derived under the assumption that the distribution of claim sizes and/or claim interarrival times belongs to the mixed Erlang class. In the final section we discuss the implementation of the methods in a number of examples using computer algebra software. These examples illustrate the efficiency of the methods even in fairly complicated cases.     

Ergodicity and First Passage Probability of Regime-Switching Geometric Brownian Motions

A regime-switching geometric Brownian motion is used to model a geometric Brownian motion with its coefficients changing randomly according to a Markov chain. In this work, the author gives a complete characterization of the recurrent property of this process. The long time behavior of this process such as its p-th moment is also studied. Moreover, the quantitative properties of the regime-switching geometric Brownian motion with two-state switching are investigated to show the difference between geometric Brownian motion with switching and without switching. At last, some estimates of its first passage probability are established.