A Note on Strong Convergence of Sums of Dependent Random Variables

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.

Strong 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.

On the Complete Convergence ofWeighted Sums for Dependent Random Variables

We study the limiting behavior of weighted sums for negatively associated (NA) random variables. We extend results in Wu (1999) and a theorem in Chow and Lai (1973) for NA random variables.

On Strong Convergence for Sums of Dependent Random Variables

Strong laws of large numbers (SLLN), laws of iterated logarithm (LIL) and other forms of asymptotic results for independent and identically distributed (iid) random variables are well understood; see Gnedenko and Kolmogorov (1954), Chow and Teicher (1988) among others. There have been many efforts in generalizing those results to dependent random variables. Representative examples are Stout (19...

A Note on Strong Convergence of Sums of Dependent Random Variables