par Gabrys, R.;Hörmann, Siegfried 
;Kokoszka, P.
Référence Journal of Time Series Econometrics, 5, page (87-116)
Publication Publié, 2013
;Kokoszka, P.Référence Journal of Time Series Econometrics, 5, page (87-116)
Publication Publié, 2013
Article révisé par les pairs
| Résumé : | A functional time series consists of curves, typically one curve per day. The most important parameter of such a series is the mean curve. We propose two methods of detecting a change in the mean function of a functional time series. The change is detected on line, as new functional observations arrive. The general methodology is motivated by, and applied to, the detection of a change in the mean intradayvolatility pattern. The methodology is asymptotically justified by applying a new notion of weak dependence for functional time series. It is calibrated and validated by simulations based on real intraday volatility curves |
