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The Marcinkiewicz Strong Law,$\displaystyle\lim_{n\to\infty}\frac{1}{n^{\frac1p}}\sum_{k=1}^n (D_{k}- D)=0$a.s. with $p\in(1,2)$, is studied for outer products $D_k=X_k\overline{X}_k^T$,where $\{X_k\},\{\overline{X}_k\}$ are both two-sided (multivariate) linearprocesses ( with coefficient matrices $(C_l), (\overline{C}_l)$ and i.i.d.\zero-mean innovations $\{\Xi\}$, $\{\overline{\Xi}\}$). Matrix sequences $C_l$and $\overline{C}_l$ can decay slowly enough (as $|l|\to\infty$) that$\{X_k,\overline{X}_k\}$ have long-range dependence while $\{D_k\}$ can haveheavy tails. In particular, the heavy-tail and long-range-dependence phenomenafor $\{D_k\}$ are handled simultaneously and a new decoupling property isproved that shows the convergence rate is determined by the worst of theheavy-tails or the long-range dependence, but not the combination. The mainresult is applied to obtain Marcinkiewicz Strong Law of Large Numbers forstochastic approximation, non-linear functions forms and autocovariances.

Marcinkiewicz Law of Large Numbers for Outer-products of Heavy-tailed, Long-range Dependent Data