- Local Trigonometric Methods for Time Series Smoothing.
- Gentile, Maria <1981>
Subject
- SECS-S/01 Statistica
Description
- The thesis is concerned with local trigonometric regression methods. The aim was to develop a method for extraction of cyclical components in time series. The main results of the thesis are the following. First, a generalization of the filter proposed by Christiano and Fitzgerald is furnished for the smoothing of ARIMA(p,d,q) process. Second, a local trigonometric filter is built, with its statistical properties. Third, they are discussed the convergence properties of trigonometric estimators, and the problem of choosing the order of the model. A large scale simulation experiment has been designed in order to assess the performance of the proposed models and methods. The results show that local trigonometric regression may be a useful tool for periodic time series analysis.
Date
- 2014-05-15
Type
- Doctoral Thesis
- PeerReviewed
Format
- application/pdf
Identifier
urn:nbn:it:unibo-12879
Gentile, Maria (2014) Local Trigonometric Methods for Time Series Smoothing. , [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Metodologia statistica per la ricerca scientifica