Results 11 to 20 of about 226 (153)
Berry-Esséen bound of sample quantiles for negatively associated sequence
Journal of Inequalities and Applications, 2011 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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General Weak Laws of Large Numbers for Bootstrap Sample Means [PDF]
, 2004 AMS classifications: 60F05, 62G09 ...
Andrew Rosalsky +3 more
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Precise lim sup behavior of probabilities of large deviations for sums of i.i.d. random variables
International Journal of Mathematics and Mathematical Sciences, Volume 2004, Issue 66, Page 3565-3576, 2004., 2004 Let {X, Xn; n ≥ 1} be a sequence of real‐valued i.i.d. random variables and let Sn=∑i=1nXi, n ≥ 1. In this paper, we study the probabilities of large deviations of the form P(Sn > tn1/p), P(Sn < −tn1/p), and P(|Sn| > tn1/p), where t > 0 and 0 < p < 2.
Deli Li, Andrew Rosalsky
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On multiple‐particle continuous‐time random walks
Journal of Applied Mathematics, Volume 2004, Issue 3, Page 213-233, 2004., 2004 Scaling limits of continuous‐time random walks are used in physics to model anomalous diffusion in which particles spread at a different rate than the classical Brownian motion. In this paper, we characterize the scaling limit of the average of multiple particles, independently moving as a continuous‐time random walk.
Peter Becker-Kern, Hans-Peter Scheffler
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Open Mathematics, 2020 In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu +3 more
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Cauchy approximation for sums of independent random variables
International Journal of Mathematics and Mathematical Sciences, Volume 2003, Issue 17, Page 1055-1066, 2003., 2003 We use Stein′s method to find a bound for Cauchy approximation. The random variables which are considered need to be independent.
K. Neammanee
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A zero‐inflated occupancy distribution: exact results and Poisson convergence
International Journal of Mathematics and Mathematical Sciences, Volume 2003, Issue 28, Page 1771-1782, 2003., 2003 We introduce the generalized zero‐inflated allocation scheme of placing n labeled balls into N labeled cells. We study the asymptotic behavior of the number of empty cells when (n, N) belongs to the “right” and “left” domain of attraction. An application to the estimation of characteristics of agreement among a set of raters which independently ...
Nikolai Kolev, Ljuben Mutafchiev
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A nonuniform bound for the approximation of Poisson binomial by Poisson distribution
International Journal of Mathematics and Mathematical Sciences, Volume 2003, Issue 48, Page 3041-3046, 2003., 2003 It is well known that Poisson binomial distribution can be approximated by Poisson distribution. In this paper, we give a nonuniform bound of this approximation by using Stein‐Chen method.
K. Neammanee
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A survey of limit laws for bootstrapped sums
International Journal of Mathematics and Mathematical Sciences, Volume 2003, Issue 45, Page 2835-2861, 2003., 2003 Concentrating mainly on independent and identically distributed (i.i.d.) real‐valued parent sequences, we give an overview of first‐order limit theorems available for bootstrapped sample sums for Efron′s bootstrap. As a light unifying theme, we expose by elementary means the relationship between corresponding conditional and unconditional bootstrap ...
Sándor Csörgő, Andrew Rosalsky
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Almost sure central limit theorems for strongly mixing and associated random variables
International Journal of Mathematics and Mathematical Sciences, Volume 29, Issue 3, Page 125-131, 2002., 2002 We prove an almost sure central limit theorem (ASCLT) for strongly mixing sequence of random variables with a slightly slow mixing rate α(n) = O((loglogn)−1−δ). We also show that ASCLT holds for an associated sequence of random variables without a stationarity assumption.
Khurelbaatar Gonchigdanzan
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