Strong laws of large numbers for arrays of rowwise independent random variables

On complete convergence in Marcinkiewicz-Zygmund type SLLN for negatively associated random variables

“…This ends the proof. Putting α = 1 t and p = 2t for 0 < t < 2 we get the corresponding result of Hu, Móricz and Taylor [6] for a sequence of negatively associated random variables which need not be identically distributed.…”

On the Strong Law of Large Numbers for Weighted Sums of Arrays of Rowwise Negatively Dependent Random Variables

“…Hu et al [5] had obtained the following result in complete convergence and they had established (1.3) for non identcally random variable when no assumption of independence between rows of the array is made.…”

On complete convergence for arrays of rowwise dependent random variables

“…1, > Many authors generalized and extended this result without assumption of identical distribution in several directions. They studied the cases of independent, stochastically dominated random variables, triangular arrays of rowwise independent, stochastically dominated in the Cesaro sense random variables and sequences of independent random variables taking value in a Banach space ( Pruitt (1966), Rohatgi (1971), Hu, Moricz and Taylor (1989), Gut (1992), Wang, Bhaskara Rao 1 A c c e p t e d m a n u s c r i p t…”