A portmanteau-type test for detecting serial correlation in locally stationary functional time series
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Date
2020
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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.
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Keywords
autocovariance operator, time domain test, functional white noise, block multiplier bootstrap