Directory UMM :Data Elmu:jurnal:S:Stochastic Processes And Their Applications:Vol87.Issue1.2000:
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We employ the interlacing construction to show that the solutions ofstochastic dierential equations on manifolds which are written in Marcus canonical form and driven by
We study a discrete time Markov process with particles being able to perform discrete time random walks and create new particles, known as branching random walk (BRW).. We suppose
i.e. intervals in 1-D, are closed intervals so that touching grains have an end-point in common.) To see this, observe that any point t ∈ U is not covered because the grains
Applying this lemma, one can conclude that, for example, the normal distribution, Weibull distributions with the parameter p¿ 1 and Poisson distribution have a light right tail..
In this section we will show (i) that the zero-avoiding transition probabilities (3) are just non-coincidence probabilities of a set of independent and dissimilar Poisson pro-
Hong (1995) has shown that if X 1 ; X 2 ; : : : are jointly symmetric, pairwise independent and identically distributed with a nite second moment, then the central limit theorem
We will study several conditionings of super Brownian motion that t into this framework, in that the conditioned process can be broken into two pieces, one of which is such a
(17) } (19) we can conclude that the long-run supply of livestock and the long-run demand for manure applied on the " eld rise with an increase in the social discount rate or
