Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/233728 
Year of Publication: 
2019
Citation: 
[Journal:] Journal of Time Series Analysis [ISSN:] 1467-9892 [Volume:] 41 [Issue:] 2 [Publisher:] John Wiley & Sons, Ltd [Place:] Oxford, UK [Year:] 2019 [Pages:] 210-228
Publisher: 
John Wiley & Sons, Ltd, Oxford, UK
Abstract: 
A class of circular processes based on Gaussian subordination is introduced. This allows for flexible modelling of directional time series with long-range dependence. Based on limit theorems for subordinated processes and consistent estimation of nuisance parameters, asymptotic confidence intervals for the mean direction are derived. Extensions to cases where the direction depends on explanatory variables are also considered. Simulations and a data example illustrate the proposed method.
Subjects: 
Circular time series
mean direction
long‐range dependence
Gaussian subordination
confidence interval
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article
Document Version: 
Published Version

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