The branching process in a brownian excursion
We give an improved quantitative version of the Kendall theorem. The Kendall theorem states that under mild conditions imposed on a probability distribution on the positive integers (i.e. a probability sequence) one can prove convergence of its renewal sequence. Due to the well-known property (the first entrance last exit decomposition) such results are of interest in the stability theory of time-homogeneous Markov chains. In particular this approach may be used to measure rates of convergence of...
In this paper we consider heavy tailed Markov renewal processes and we prove that, suitably renormalised, they converge in law towards the -stable regenerative set. We then apply these results to the strip wetting model which is a random walk constrained above a wall and rewarded or penalized when it hits the strip where is a given positive number. The convergence result that we establish allows to characterize the scaling limit of this process at criticality.
We consider regenerative processes with values in some general Polish space. We define their -big excursions as excursions such that , where is some given functional on the space of excursions which can be thought of as, e.g., the length or the height of . We establish a general condition that guarantees the convergence of a sequence of regenerative processes involving the convergence of -big excursions and of their endpoints, for all in a set whose closure contains . Finally, we provide...
Let us consider two independent renewal processes generated by appropriate sequences of life times. We say that a renewal time is accepted if in the time between a signal and the preceding one, some signal of the second process occurs. Our purpose is to analyze the sequences of accepted renewals. For simplicity we consider continuous and discrete time separately. In the first case we mainly consider the renewal process rarefied by the Poisson process, in the second we analyze the process generated...
A simple renewal process is a stochastic process taking values in where the lengths of the runs of ’s between successive zeros are independent and identically distributed. After observing one would like to estimate the time remaining until the next occurrence of a zero, and the problem of universal estimators is to do so without prior knowledge of the distribution of the process. We give some universal estimates with rates for the expected time to renewal as well as for the conditional distribution...