A portmanteau-type test for detecting serial correlation in locally stationary functional time series

Axel Bücher (), Holger Dette () and Florian Heinrichs ()
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Axel Bücher: Heinrich-Heine-Universität Düsseldorf
Holger Dette: Ruhr-Universität Bochum
Florian Heinrichs: Ruhr-Universität Bochum

Statistical Inference for Stochastic Processes, 2023, vol. 26, issue 2, No 2, 255-278

Abstract: Abstract The portmanteau test provides the vanilla method for detecting serial correlations in classical univariate time series analysis. The method is extended to the case of observations from a locally stationary functional time series. Asymptotic critical values are obtained by a suitable block multiplier bootstrap procedure. The test is shown to asymptotically hold its level and to be consistent against general alternatives.

Keywords: Autocovariance operator; Block multiplier bootstrap; Functional white noise; Time domain test (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11203-022-09285-5

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