Directory UMM :Data Elmu:jurnal:S:Stochastic Processes And Their Applications:Vol90.Issue1.2000:
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In this paper, we study small ball probabilities for Gaussian Markov processes under the L p -norms, which can also be viewed as for Brownian motion under weighted.. L
The topic of estimating rates of convergence in the functional central limit theorem (FCLT) for martingales has been studied for a long time, but optimal results were found only
We introduce two notions of asymptotic exponentiality in variance and asymptotic independence and we study their implications on the asymptotics of the mean value of this hitting
We propose a class of Dirichlet forms corresponding to spatially inhomogeneous processes which covers a family of Dirichlet forms described by modied derivatives similarly to the
To begin, we state a technical Lemma, involving controls on the law of some killed processes: this result is crucial to handle the case of measurable functions f for the analysis of
It is not dicult to see that the most general classical branching processes that are Markovian in the age structure are those outlined in the introduction, combining a
Sucient conditions for the large deviation principle (LDP) as well as for the moderate devia- tions principle (MDP) for U -processes in the so-called non-degenerate case are proved
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
