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Temporal Forecasting with a Bayesian Spatial Predictor : Application to Ozone
Joint Authors
Dou, Yiping
Zidek, James V.
Le, Nhu D.
Source
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-01
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper develops and empirically compares two Bayesian and empirical Bayes space-time approaches for forecasting next-day hourly ground-level ozone concentrations.
The comparison involves the Chicago area in the summer of 2000 and measurements from fourteen monitors as reported in the EPA's AQS database.
One of these approaches adapts a multivariate method originally designed for spatial prediction.
The second is based on a state-space modeling approach originally developed and used in a case study involving one week in Mexico City with ten monitoring sites.
The first method proves superior to the second in the Chicago Case Study, judged by several criteria, notably root mean square predictive accuracy, computing times, and calibration of 95% predictive intervals.
American Psychological Association (APA)
Dou, Yiping& Le, Nhu D.& Zidek, James V.. 2012. Temporal Forecasting with a Bayesian Spatial Predictor : Application to Ozone. Advances in Meteorology،Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-453243
Modern Language Association (MLA)
Dou, Yiping…[et al.]. Temporal Forecasting with a Bayesian Spatial Predictor : Application to Ozone. Advances in Meteorology No. 2012 (2012), pp.1-13.
https://search.emarefa.net/detail/BIM-453243
American Medical Association (AMA)
Dou, Yiping& Le, Nhu D.& Zidek, James V.. Temporal Forecasting with a Bayesian Spatial Predictor : Application to Ozone. Advances in Meteorology. 2012. Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-453243
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453243