Inequalities for the mean exit time from an interval for a random walk

2021 ◽  
Vol 85 (4) ◽  
Author(s):  
Vladimir Ivanovich Lotov
2008 ◽  
Vol 08 (03) ◽  
pp. 583-591 ◽  
Author(s):  
ZHIHUI YANG ◽  
JINQIAO DUAN

A dynamical system driven by non-Gaussian Lévy noises of small intensity is considered. The first exit time of solution orbits from a bounded neighborhood of an attracting equilibrium state is estimated. For a class of non-Gaussian Lévy noises, it is shown that the mean exit time is asymptotically faster than exponential (the well-known Gaussian Brownian noise case) but slower than polynomial (the stable Lévy noise case), in terms of the reciprocal of the small noise intensity.


Science ◽  
2021 ◽  
Vol 372 (6547) ◽  
pp. eaay4895
Author(s):  
Babak M. S. Arani ◽  
Stephen R. Carpenter ◽  
Leo Lahti ◽  
Egbert H. van Nes ◽  
Marten Scheffer

Ecological resilience is the magnitude of the largest perturbation from which a system can still recover to its original state. However, a transition into another state may often be invoked by a series of minor synergistic perturbations rather than a single big one. We show how resilience can be estimated in terms of average life expectancy, accounting for this natural regime of variability. We use time series to fit a model that captures the stochastic as well as the deterministic components. The model is then used to estimate the mean exit time from the basin of attraction. This approach offers a fresh angle to anticipating the chance of a critical transition at a time when high-resolution time series are becoming increasingly available.


1978 ◽  
Vol 15 (1) ◽  
pp. 13-25 ◽  
Author(s):  
Allan H. Marcus ◽  
Stanley Czajkowski

Linear and non-linear secondary Poisson process models are developed for the level of carboxyhemoglobin in cigarette smoking. The moments of the time of first exit above a critical threshold are expanded as power series in the initial state of the process. Recurrence relations for the coefficients in the moment series are solved numerically. An explicit formula involving Poisson probability functions is obtained for the mean exit time of shot noise.


2006 ◽  
pp. 137-141
Author(s):  
Jaume Masoliver ◽  
Miquel Montero ◽  
Josep Perelló
Keyword(s):  

2009 ◽  
Vol 16 (04) ◽  
pp. 325-350 ◽  
Author(s):  
Mario Abundo

For a, b > 0, we consider a temporally homogeneous, one-dimensional diffusion process X(t) defined over I = (-b, a), with infinitesimal parameters depending on the sign of X(t). We suppose that, when X(t) reaches the position 0, it is reflected rightward to δ with probability p > 0 and leftward to -δ with probability 1 - p, where δ > 0. Closed analytical expressions are found for the mean exit time from the interval (-b, a), and for the probability of exit through the right end a, in the limit δ → 0+, generalizing the results of Lefebvre, holding for asymmetric Wiener process. Moreover, in alternative to the heavy analytical calculations, a numerical method is presented to estimate approximately the quantities above. Furthermore, on the analogy of skew Brownian motion, the notion of skew diffusion process is introduced. Some examples and numerical results are also reported.


2018 ◽  
Vol 18 (03) ◽  
pp. 1850025
Author(s):  
Xinyong Zhang ◽  
Hui Wang ◽  
Yanjie Zhang ◽  
Haokun Lin

This paper is devoted to studying parameter estimation for a class of stochastic dynamical systems with oscillating coefficients. We show that the homogenized systems faithfully capture the dynamical quantities such as mean exit time and escape probability. Exacting data from observations on the mean exit time (or escape probability) of the original systems, we try to fit the mean exit time (or escape probability) of the homogenized systems by least square method. In this way, we can accurately estimate the unknown parameter in the drift under appropriate assumptions. Furthermore, we conduct some numerical experiments to illustrate our method.


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