Authors: Axt, Ieva
Fried, Roland
Title: On variance estimation under shifts in the mean
Language (ISO): en
Abstract: In many situations, it is crucial to estimate the variance properly. Ordinary variance estimators perform poorly in the presence of shifts in the mean. We investigate an approach based on non-overlapping blocks, which yields good results in change-point scenarios. We show the strong consistency and the asymptotic normality of such blocks-estimators of the variance under independence. Weak consistency is shown for short-range dependent strictly stationary data. We provide recommendations on the appropriate choice of the block size and compare this blocks-approach with difference-based estimators. If level shifts occur frequently and are rather large, the best results can be obtained by adaptive trimming of the blocks.
Subject Headings: Blockwise estimation
Trimmed mean
Issue Date: 2020-04-01
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Appears in Collections:Lehrstuhl Mathematische Statistik und naturwissenschaftliche Anwendungen

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