A Blockwise Bootstrap-Based Two-Sample Test for High-Dimensional Time Series
Lin Yang
Abstract:We propose a two-sample testing procedure for high-dimensional time series. To obtain the asymptotic distribution of our ℓ∞-type test statistic under the null hypothesis, we establish high-dimensional central limit theorems (HCLTs) for an α-mixing sequence. Specifically, we derive two HCLTs for the maximum of a sum of high-dimensional α-mixing random vectors under the assumptions of bounded finite moments and exponential tails, respectively. The proposed HCLT for α-mixing sequence under bounded finite moments … Show more
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