Joint Econometrics and Statistics Workshop
Detection of periodicity in functional time series
Siegfried H÷rmann (UniversitÚ libre de Bruxelles)
Friday 24 February 2017 12:00 - 13:00
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About this event
Periodicity is one of the most important characteristics of time series, and tests for periodicity go back to the very origins of the eld. The importance of such tests has manifold reason. One of them is that most inferential pro-cedures require that the series be stationary, but classical stationarity tests (as e.g. KPSS procedures) have little power against a periodic component inthe mean. In this account we respond to the need to develop periodicity tests for functional time series (FTS). Examples of FTS's include annual temperature or smoothed precipitation curves, daily pollution level curves, various daily curves derived from high frequency asset price data, daily bond yield curves, daily vehicle trac curves and many others. One of the important contributions of this article is the development of a fully functional ANOVA test for stationary data. If the functional time series (Yt) satises a certain weak-dependence condition, then, using a fre- quency domain approach, we obtain the asymptotic null-distribution (for the constant mean hypothesis) of the functional ANOVA statistic. The limiting distribution has an interesting form and can be written as a sum of independent hypoexponential variables whose parameters are eigenvalues of the spectral density operator of (Yt).
Econometrics and Statistics seminars are held on Fridays in term time at 12:00-13:00, ONLINE, unless specified otherwise.
Seminar organisers: Dr Tatiana Komarova and Dr Yunxiao Chen.
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