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• W2890775074 abstract "The goal of this paper is to obtain expectation bounds for the deviation of large sample autocovariance matrices from their means under weak data dependence. While the accuracy of covariance matrix estimation corresponding to independent data has been well understood, much less is known in the case of dependent data. We make a step towards filling this gap, and establish deviation bounds that depend only on the parameters controlling the intrinsic dimension of the data up to some logarithmic terms. Our results have immediate impacts on high dimensional time series analysis, and we apply them to high dimensional linear VAR($d$) model, vector-valued ARCH model, and a model used in Banna et al. (2016)." @default.
• W2890775074 created "2018-09-27" @default.
• W2890775074 creator A5021528850 @default.
• W2890775074 creator A5028956096 @default.
• W2890775074 date "2018-09-24" @default.
• W2890775074 modified "2023-09-23" @default.
• W2890775074 title "Moment bounds for large autocovariance matrices under dependence" @default.
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• W2890775074 doi "https://doi.org/10.48550/arxiv.1809.08760" @default.
• W2890775074 hasPublicationYear "2018" @default.
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