Convergence in $$\varvec{p}$$ p -Mean for Arrays of Random Variables

Complete Moment Convergence and Mean Convergence for Arrays of Rowwise Extended Negatively Dependent Random Variables

The authors first present a Rosenthal inequality for sequence of extended negatively dependent (END) random variables. By means of the Rosenthal inequality, the authors obtain some complete moment convergence and mean convergence results for arrays of rowwise END random variables. The results in this paper extend and improve the corresponding theorems by Hu and Taylor (1997).

Dominated Convergence for Fuzzy Random Variables

Fuzzy Confidence Intervals for Mean of Fuzzy Random Variables

This article has no abstract.

On the LP-convergence for multidimensional arrays of random variables

Let Z+, where d is an integer, denote the positive integer d-dimensional lattice points. The notation m≺ n, where m= (m1,m2, . . . ,md) and n= (n1,n2, . . . ,nd) ∈ Z+, means that mi ≤ ni, 1 ≤ i≤ d, |n| is used for ∏d i=1ni. Gut [2] proved that if {X ,Xn, n∈ Z+} is a d-dimensional array of i.i.d. random variables with E|X|p <∞ (0 < p < 2) and EX = 0 if 1 ≤ p < 2, then ∑ j≺nXj |n|1/p −→ 0 in L p ...

On complete convergence for arrays of rowwise dependent random variables

This paper establishes two results for complete convergence in the law of large numbers for arrays under %-mixing and ~ %-mixing association in rows. They extend several known results. AMS classi cation: 60F15