Open Access
2023 White noise testing for functional time series
Mihyun Kim, Piotr Kokoszka, Gregory Rice
Author Affiliations +
Statist. Surv. 17: 119-168 (2023). DOI: 10.1214/23-SS143


We review white noise tests in the context of functional time series, and compare many of them using a custom developed R package wwntests. The tests are categorized based on whether they are conducted in the time domain or spectral domain, and whether they are valid for i.i.d. or general uncorrelated noise. We also review and extend several residual-based goodness-of-fit tests of popular models used in functional data analysis. Through numerous simulation experiments and a data application, we demonstrate the use of these tests, and are able to provide practical guidance on their implementation, benefits, and drawbacks.


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Mihyun Kim. Piotr Kokoszka. Gregory Rice. "White noise testing for functional time series." Statist. Surv. 17 119 - 168, 2023.


Received: 1 August 2022; Published: 2023
First available in Project Euclid: 12 May 2023

MathSciNet: MR4587447
zbMATH: 07690330
Digital Object Identifier: 10.1214/23-SS143

Vol.17 • 2023
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