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CSDA
2006
191views more  CSDA 2006»
13 years 4 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms
WCE
2007
13 years 5 months ago
Building Time Series Forecasting Model By Independent Component Analysis Mechanism
—Building a time series forecasting model by independent component analysis mechanism presents in the paper. Different from using the time series directly with the traditional A...
Jin-Cherng Lin, Yung-Hsin Li, Cheng-Hsiung Liu
IJCNN
2007
IEEE
13 years 10 months ago
Local Learning of Tide Level Time Series using a Fuzzy Approach
— Forecasting the tide level in the Venezia lagoon is a very compelling task. In this work we propose a new approach to the learning of tide level time series based on the local ...
E. Canestrelli, P. Canestrelli, Marco Corazza, Mau...
CSDA
2008
98views more  CSDA 2008»
13 years 4 months ago
Forecasting binary longitudinal data by a functional PC-ARIMA model
The purpose of this paper is to forecast the time evolution of a binary response variable from an associated continuous time series observed only at discrete time points that usual...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
NPL
2011
12 years 7 months ago
A Neural Network Scheme for Long-Term Forecasting of Chaotic Time Series
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster...
Pilar Gómez-Gil, Juan Manuel Ramírez...