Results 31 to 40 of about 2,873 (97)
On the paper ``Weak convergence of some classes of martingales with jumps''
This note extends some results of Nishiyama [Ann. Probab. 28 (2000) 685--712]. A maximal inequality for stochastic integrals with respect to integer-valued random measures which may have infinitely many jumps on compact time intervals is given.
Nishiyama, Yoichi
core +1 more source
asymptotics for open‐loop window flow control
An open‐loop window flow‐control scheme regulates the flow into a system by allowing at most a specified window size W of flow in any interval of length L. The sliding window considers all subintervals of length L, while the jumping window considers consecutive disjoint intervals of length L.
Arthur W. Berger, Ward Whitt
wiley +1 more source
Global Central Limit Theorems for Stationary Markov Chains
Let P be a Markov operator on a general state space (S, Σ) with an invariant probability measure m, assumed to be ergodic. We study conditions which yield that for every centered non-zero f ∈ L2(m) a non-degenerate annealed CLT and an L2-normalized CLT ...
Lin Michael
doaj +1 more source
On the weak law of large numbers for normed weighted sums of I.I.D. random variables
For weighted sums of independent and identically distributed random variables {Yn, n ≥ 1}, a general weak law of large numbers of the form is established where {νn, n ≥ 1} and {bn, n ≥ 1} are statable constants. The hypotheses involve both the behavior of the tail of the distribution of |Y1| and the growth behaviors of the constants {an, n ≥ 1} and {bn,
André Adler, Andrew Rosalsky
wiley +1 more source
Central Limit Theorem for Random “Contractive” Functions on Interval
We use the approach from Czudek and Szarek (see [1]) to prove the central limit theorem for a stationary Markov chain generated by an iterative function system for a family of increasing, injective functions on [0, 1] with “contractive” properties.
Block Maciej +2 more
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On a probability problem connected with Railway traffic
Let Fn(x) and Gn(x) be the empirical distribution functions of two independent samples, each of size n, in the case where the elements of the samples are independent random variables, each having the same continuous distribution function V(x) over the interval (0, 1). Define a statistic θn by .
Lajos Takács
wiley +1 more source
Oscillations of empirical distribution functions under dependence
We obtain an almost sure bound for oscillation rates of empirical distribution functions for stationary causal processes. For short-range dependent processes, the oscillation rate is shown to be optimal in the sense that it is as sharp as the one ...
Wu, Wei Biao
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On the distribution of the number of vertices in layers of random trees
Denote by Sn the set of all distinct rooted trees with n labeled vertices. A tree is chosen at random in the set Sn, assuming that all the possible nn−1 choices are equally probable. Define τn(m) as the number of vertices in layer m, that is, the number of vertices at a distance m from the root of the tree. The distance of a vertex from the root is the
Lajos Takács
wiley +1 more source
The quenched limiting distributions of a one-dimensional random walk in random scenery
For a one-dimensional random walk in random scenery (RWRS) on Z, we determine its quenched weak limits by applying Strassen's functional law of the iterated logarithm. As a consequence, conditioned on the random scenery, the one-dimensional RWRS does not
Guillotin-Plantard, Nadine +2 more
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Berry-Esséen bound of sample quantiles for negatively associated sequence
In this paper, we investigate the Berry-Esséen bound of the sample quantiles for the negatively associated random variables under some weak conditions. The rate of normal approximation is shown as O(n -1/9). 2010 Mathematics Subject Classification:
Zhang Qinchi +3 more
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