Note on the complete moment convergence of maximal partial sums for moving average process under sublinear expectations

In this paper, the complete moment convergence for the maximal partial sums of moving average processes generated by $\{Y_i,-\mathrm{\infty }<i<\mathrm{\infty }\}$ is proved under conditions that $C_{\mathbb{V}}\left(|Y_1{|}^p\left(1\vee l(f^{-1}(Y_1))\right)\right)<\mathrm{\infty }$, where $f^{-1}$ is the inverse function of $f$, and $\{Y_i,-\mathrm{\infty }<i<\mathrm{\infty }\}$ is a double sequence of identically distributed, negatively dependent random variables under sublinear expectations. The results established in sublinear expectation spaces complement and extend the corresponding ones in probability space in some extent.