DocumentCode
2861009
Title
Notice of Retraction
Mixture Periodic Autoregressive Moving Average model with application to PM10 concentrations
Author
Huizhan Wang ; Fangan Deng
Author_Institution
Dept. of Math., Shaanxi Univ. of Technol., Hanzhong, China
Volume
14
fYear
2010
fDate
22-24 Oct. 2010
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
We generalize the Mixture Periodic Autoregressive (MPAR) model introduced by Shao to the Mixture Periodic Autoregressive Moving Average (MPARMA) model for the modelling nonlinear time series. The stationarity is derived. The estimation is done via EM algorithm and the model selection criterion is given. The model is illustrated by analyzing the particulate matter concentrations in Cleveland, OH.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
We generalize the Mixture Periodic Autoregressive (MPAR) model introduced by Shao to the Mixture Periodic Autoregressive Moving Average (MPARMA) model for the modelling nonlinear time series. The stationarity is derived. The estimation is done via EM algorithm and the model selection criterion is given. The model is illustrated by analyzing the particulate matter concentrations in Cleveland, OH.
Keywords
atmospheric composition; geophysical techniques; time series; Cleveland; EM algorithm; OH; PM10 concentrations; USA; mixture periodic autoregressive moving average model; nonlinear time series; particulate matter concentrations; Histograms; Out of order; Yttrium; BIC; EM algorithm; Mixture Periodic Autoregressive Moving Average Models; periodically correlated time series;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location
Taiyuan
Print_ISBN
978-1-4244-7235-2
Type
conf
DOI
10.1109/ICCASM.2010.5622419
Filename
5622419
Link To Document