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Document type:
Zeitungsartikel 
Author(s):
Aue, A. and Klepsch, J. 
Title:
Estimating functional time series by moving average model fitting 
Abstract:
Functional time series have become an integral part of both functional data and time series analysis. Important contributions to methodology, theory and application for the prediction of future trajectories and the estimation of functional time series parameters have been made in the recent past. This paper continues this line of research by proposing a first principled approach to estimate invertible functional time series by fitting functional moving average processes. The idea is to estimat...    »
 
Keywords:
Dimension reduction; Estimation, Functional data analysis; Functional linear process; Functional time series, Hilbert spaces; Innovations Algorithm, Moving average process 
Journal title:
Preprint 
Year:
2017 
Year / month:
2017-01 
Quarter:
1. Quartal 
Month:
Jan 
WWW:
_blank 
Status:
Preprint / submitted 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text