Strong Laws for Weighted Sums of Negative Dependent Random Variables
Authors: not saved
Abstract:
In this paper, we discuss strong laws for weighted sums of pairwise negatively dependent random variables. The results on i.i.d case of Soo Hak Sung [9] are generalized and extended.
similar resources
strong laws for weighted sums of negative dependent random variables
in this paper, we discuss strong laws for weighted sums of pairwise negatively dependent random variables. the results on i.i.d case of soo hak sung [9] are generalized and extended.
full textStrong Convergence of Weighted Sums for Negatively Orthant Dependent Random Variables
We discuss in this paper the strong convergence for weighted sums of negatively orthant dependent (NOD) random variables by generalized Gaussian techniques. As a corollary, a Cesaro law of large numbers of i.i.d. random variables is extended in NOD setting by generalized Gaussian techniques.
full textStrong Laws for Weighted Sums of I.i.d. Random Variables
Strong laws are established for linear statistics that are weighted sums of a random sample. We show extensions of the Marcinkiewicz-Zygmund strong laws under certain moment conditions on both the weights and the distribution. The result obtained extends and sharpens the result of Sung.
full textAsymptotic Behavior of Weighted Sums of Weakly Negative Dependent Random Variables
Let be a sequence of weakly negative dependent (denoted by, WND) random variables with common distribution function F and let be other sequence of positive random variables independent of and for some and for all . In this paper, we study the asymptotic behavior of the tail probabilities of the maximum, weighted sums, randomly weighted sums and randomly indexed weighted sums of heavy...
full textstrong convergence of weighted sums for negatively orthant dependent random variables
we discuss in this paper the strong convergence for weighted sums of negatively orthant dependent (nod) random variables by generalized gaussian techniques. as a corollary, a cesaro law of large numbers of i.i.d. random variables is extended in nod setting by generalized gaussian techniques.
full textStrong Laws of Large Numbers for Weighted Sums of Negatively Dependent Random Variables
For double arrays of constants {ani, 1 ≤ i ≤ kn, n ≥ 1} and sequences of negatively orthant dependent random variables {Xn, n ≥ 1}, the conditions for strong law of large number of ∑kn i=1 aniXi are given. Both cases kn ↑ ∞ and kn = ∞ are treated.
full textMy Resources
Journal title
volume 16 issue 3
pages -
publication date 2005-09-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023