The aim of this paper is to investigate results on almost sure convergence weighted sums coordinatewise pairwise negatively quadrant dependent random variables taking values in Hilbert spaces. As an application, the degenerate von Mises-statistics investigated.
 Keywords: Negative dependence, spaces, Weighted sums, Strong laws large numbers. 

in this paper, strong laws of large numbers (slln) are obtained for the sums ƒ°=nii x1, undercertain conditions, where {x ,n . 1} n is a sequence of pairwise negatively dependent random variables.

In this paper, the concepts of positive dependence and linearlypositive quadrant dependence are introduced for fuzzy random variables. Also,an inequality is obtained for partial sums of linearly positive quadrant depen-dent fuzzy random variables. Moreover, a weak law of large numbers is estab-lished for linearly positive quadrant dependent fuzzy random variables. Weextend some well known inequ...

in the following work we present a proof for the strong law of large numbers for pairwise negatively dependent random variables which relaxes the usual assumption of pairwise independence. let be a double sequence of pairwise negatively dependent random variables. if for all non-negative real numbers t and , for 1 < p < 2, then we prove that (1). in addition, it also converges to 0 in . the res...

let be a stationary sequence of pair wise negative quadrant dependent random variables with survival function {,1}nxn?f(x)=p[x>x]. the empirical survival function ()nfx based on 12,,...,nxxx is proposed as an estimator for ()nfx. strong consistency and point wise as well as uniform of ()nfx are discussed

in this paper, we obtain the upper exponential bounds for the tail probabilities of the quadratic forms for negatively dependent subgaussian random variables. in particular the law of iterated logarithm for quadratic forms of independent subgaussian random variables is generalized to the case of negatively dependent subgaussian random variables.

In the following work we present a proof for the strong law of large numbers for pairwise negatively dependent random variables which relaxes the usual assumption of pairwise independence. Let be a double sequence of pairwise negatively dependent random variables. If for all non-negative real numbers t and , for 1 < p < 2, then we prove that (1). In addition, it also converges to 0 in ....

* Correspondence: [email protected] School of Mathematics Science, University of Electronic Science and Technology of China, Chengdu 610054, PR China Full list of author information is available at the end of the article Abstract In this paper, complete convergence and strong law of large numbers for sequences of pairwise negatively quadrant dependent (NQD) random variables with nonidenti...

In this paper, we obtain some Rosenthal’s type inequalities for negatively orthant dependent (NOD) random variables.

Let be a stationary sequence of pair wise negative quadrant dependent random variables with survival function {,1}nXn?F(x)=P[X>x]. The empirical survival function ()nFx based on 12,,...,nXXX is proposed as an estimator for ()nFx. Strong consistency and point wise as well as uniform of ()nFx are discussed