Complete convergence of moving average processes produced by negatively dependent random variables under sub-linear expectations

Suppose that $\{a_i,-\mathrm{\infty }<i<\mathrm{\infty }\}$ is an absolutely summable set of real numbers, $\{Y_i,-\mathrm{\infty }<i<\mathrm{\infty }\}$ is a subset of identically distributed, negatively dependent random variables under sub-linear expectations. Here, we get complete convergence and Marcinkiewicz-Zygmund strong law of large numbers for the partial sums of moving average processes $\{X_n=\sum _{i=-\mathrm{\infty }}^{\mathrm{\infty }}{a}_i{Y}_{i+n},n\ge 1\}$ produced by $\{Y_i,-\mathrm{\infty }<i<\mathrm{\infty }\}$ of identically distributed, negatively dependent random variables under sub-linear expectations, complementing the relevant results in probability space.