On complete convergence for arrays of rowwise -mixing random variables and its applications.
Detection of outliers and patches in bilinear time series models.
On the strong laws for weighted sums of -mixing random variables.
Complete -order moment convergence of moving average processes under -mixing assumptions
Let be a doubly infinite sequence of identically distributed -mixing random variables, and an absolutely summable sequence of real numbers. We prove the complete -order moment convergence for the partial sums of moving average processes based on the sequence of -mixing random variables under some suitable conditions. These results generalize and complement earlier results.
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