Many authors have used one of the two following type of dependence: on the one hand
mixing properties, introduced by Rosenblatt (1956)[166], on the other hand martingales …

Let X n=(x ij) be an n by p data matrix, where the n rows form a random sample of size n from
a certain p-dimensional population distribution. Let R n=(ρ ij) be the p× p sample correlation …

In this paper, some basic properties for negatively superadditive-dependent (NSD, in short)
random variables are presented, such as the Rosenthal-type inequality and the Kolmogorov …

We discuss complete convergence for weighted sums of negatively associated (NA) random
variables. The result on iid case of Li et al.(J. Theoret. Probab. 8 (1995) 49–76) is …

Under general weighting coefficient, we obtain the complete convergence for weighted
sums of negatively associated (NA) sequences, and discuss its necessity. The results on iid …

We consider a testing problem for cross-sectional independence for high-dimensional panel
data, where the number of cross-sectional units is potentially much larger than the number of …

Applying to the moment inequality of negatively dependent random variables the complete
convergence for weighted sums of sequences of negatively dependent random variables is …

A complete convergence result is obtained for weighted sums of identically distributed ρ*-
mixing random variables with E| X 1| α log (1+| X 1|)<∞ for some 0< α≤ 2. This result …

Complete Convergence Theorems for Extended Negatively Dependent Random Variables
Page 1 Sankhya : The Indian Journal of Statistics 2015, Volume 77-A, Part 1, pp. 1-29 c 201 …

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