On asymptotic properties of the distribution of the number of pairs of H-connected tuples

2002 ◽  
Vol 12 (4) ◽  
Author(s):  
V. G. Mikhailov
Keyword(s):  
Asymptotic Properties ◽  
Sufficient Conditions ◽  
Basic Research ◽  
Poisson Approximation ◽  
Explicit Estimate ◽  
Research Grants ◽  
Local Variant ◽  
Sufficient Conditions For Convergence ◽  
Stein Method ◽  
Independent Identically Distributed

AbstractThe main result of this paper is a theorem about convergence of the distribution of the number of pairs of H-connected s-tuples in two independent sequences of independent identically distributed variables. The concept of H-connection is a generalisation of the concept of H-equivalence of tuples. We give sufficient conditions for convergence and an explicit estimate of the rate of convergence. We use the local variant of the Chen-Stein method for estimating the accuracy of Poisson approximation for distribution of the set of dependent random indicators. The main results of this paper were announced in [7].The research was supported by the Russian Foundation for Basic Research, grants 02-01-00266 and 00-15-96136.

scholarly journals [Poisson Approximation and the Chen-Stein Method]: Rejoinder

1990 ◽  
Vol 5 (4) ◽  
pp. 432-434 ◽  
Author(s):  
Richard Arratia ◽  
Larry Goldstein ◽  
Louis Gordon
Keyword(s):  
Poisson Approximation ◽  
Stein Method

A clustering law for some discrete order statistics

2003 ◽  
Vol 40 (01) ◽  
pp. 226-241 ◽  
Author(s):  
Sunder Sethuraman
Keyword(s):  
Distribution Function ◽  
Positive Integer ◽  
Order Statistics ◽  
Law Of Large Numbers ◽  
Asymptotic Properties ◽  
Random Variables ◽  
Large Numbers ◽  
The Law ◽  
Sample Maximum ◽  
Independent Identically Distributed

Let X 1, X 2, …, X n be a sequence of independent, identically distributed positive integer random variables with distribution function F. Anderson (1970) proved a variant of the law of large numbers by showing that the sample maximum moves asymptotically on two values if and only if F satisfies a ‘clustering’ condition, In this article, we generalize Anderson's result and show that it is robust by proving that, for any r ≥ 0, the sample maximum and other extremes asymptotically cluster on r + 2 values if and only if Together with previous work which considered other asymptotic properties of these sample extremes, a more detailed asymptotic clustering structure for discrete order statistics is presented.

The convex hull of a normal sample

1994 ◽  
Vol 26 (04) ◽  
pp. 855-875 ◽  
Author(s):  
Irene Hueter
Keyword(s):  
Central Limit Theorem ◽  
Limit Theorem ◽  
Convex Hull ◽  
Asymptotic Behaviour ◽  
Central Limit ◽  
Random Variables ◽  
Poisson Approximation ◽  
Normal Sample ◽  
Central Importance ◽  
Independent Identically Distributed

Consider the convex hull of n independent, identically distributed points in the plane. Functionals of interest are the number of vertices Nn , the perimeter Ln and the area An of the convex hull. We study the asymptotic behaviour of these three quantities when the points are standard normally distributed. In particular, we derive the variances of Nn, Ln and An for large n and prove a central limit theorem for each of these random variables. We enlarge on a method developed by Groeneboom (1988) for uniformly distributed points supported on a bounded planar region. The process of vertices of the convex hull is of central importance. Poisson approximation and martingale techniques are used.

A class of correlated cumulative shock models

1985 ◽  
Vol 17 (2) ◽  
pp. 347-366 ◽  
Author(s):  
Ushio Sumita ◽  
J. George Shanthikumar
Keyword(s):  
Failure Time ◽  
Asymptotic Properties ◽  
Sufficient Conditions ◽  
Random Variables ◽  
System Failure ◽  
Shock Models ◽  
The Times ◽  
New Better Than Used ◽  
Better Than

In this paper we define and analyze a class of cumulative shock models associated with a bivariate sequence {Xn, Yn}∞n=0 of correlated random variables. The {Xn} denote the sizes of the shocks and the {Yn} denote the times between successive shocks. The system fails when the cumulative magnitude of the shocks exceeds a prespecified level z. Two models, depending on whether the size of the nth shock is correlated with the length of the interval since the last shock or with the length of the succeeding interval until the next shock, are considered. Various transform results and asymptotic properties of the system failure time are obtained. Further, sufficient conditions are established under which system failure time is new better than used, new better than used in expectation, and harmonic new better than used in expectation.

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