Directory UMM :Data Elmu:jurnal:S:Stochastic Processes And Their Applications:Vol90.Issue2.2000:
Teks penuh
Dokumen terkait
In a previous paper (Hambly, 1997), a natural Brownian motion on a random recursive Sierpinski gasket was constructed and relatively crude estimates obtained on its transition
To compensate for this, at the end of the paper we discuss the convergence and error properties of a similar construction of fBM that uses the KMT approximation instead, which
Finally, we develop an exact sampling (or perfect simulation) algorithm for pro- ducing observations from the quasi-stationary distribution (and, more generally, from the
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 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
Note that Iosifescu and Grigorescu (1990) present a wide range of pointwise a.s., log–log laws and weak convergence results and some invariance principles for dependent
tion we study extremes of R n -valued Gaussian processes with strongly dependent component processes, and of totally skewed moving averages of -stable motions.. Further we prove
Part (ii) of Theorem 2.1, apart from being a step in the proof of part (iii), shows that the optimal estimator based on the pre-processed observations (3) can be approximated via
