论文标题
部分总和和最大值的联合功能收敛，用于移动平均，具有弱依赖的重尾创新和随机系数
Joint functional convergence of partial sums and maxima for moving averages with weakly dependent heavy-tailed innovations and random coefficients
论文作者
论文摘要
对于具有随机系数和重尾创新的移动平均过程，这些工艺在强大的混合和局部依赖条件的意义上微弱地依赖于$ d'$，我们研究了部分总和和最大值的联合功能收敛。假设一系列系数的所有部分总和均为A.S.在零和系列的总和之间，我们在$ \ mathbb {r}^{2} $的空间中得出一个功能限制定理，而skorokhod弱$ m_ {2} $ topology在$ [0，1] $上函数上的$ [0，1] $。
For moving average processes with random coefficients and heavy-tailed innovations that are weakly dependent in the sense of strong mixing and local dependence condition $D'$ we study joint functional convergence of partial sums and maxima. Under the assumption that all partial sums of the series of coefficients are a.s. bounded between zero and the sum of the series we derive a functional limit theorem in the space of $\mathbb{R}^{2}$-valued càdlàg functions on $[0, 1]$ with the Skorokhod weak $M_{2}$ topology.
