Multivariate geometric autoregressive and autoregressive moving average models

We present Autoregressive (AR) and autoregressive moving average (ARMA) processes with multivariate geometric (MG) distribution. The theory of positive dependence is used to show that in many cases, multivariate geometric autoregressive (MGAR) and multivariate autoregressive moving average (MGARMA) models consist of associated random variables. We also provide a special case of the multivariate geometric autoregressive model in which it is stationary and has multivariate geometric distribution.

Complete convergence and complete moment convergence for arrays of Rowwise asymptotically almost negatively associated random variables under the sub-linear expectations

In this article, we investigate the complete convergence and complete moment convergence for maximal partial sums of asymptotically almost negatively associated random variables under the sublinear expectations. The results obtained in the article are the extensions of the complete convergence and complete moment convergence under classical linear expectation space.