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Volumn 53, Issue 1, 2006, Pages 9-15

Spatio-temporal statistical models for river monitoring networks

Author keywords

Parameter estimation; Space time model; Theory intervention analysis; Water quality

Indexed keywords

MATHEMATICAL MODELS; MONITORING; PARAMETER ESTIMATION; RIVERS; STATE SPACE METHODS; STATISTICAL METHODS; WASTEWATER TREATMENT; WATER TREATMENT PLANTS;

EID: 33644631348     PISSN: 02731223     EISSN: None     Source Type: Book Series    
DOI: 10.2166/wst.2006.002     Document Type: Article
Times cited : (13)

References (11)
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  • 3
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    • Chunsheng, M. (2003). Nonstationary covariance functions that model space-time interactions. Statistics and Probability Letters, 61(4), 411-419.
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    • Chunsheng, M.1
  • 5
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    • Spatio-temporal prediction of snow water equivalent using the Kalman filter
    • Huang, H. and Cressie, N. (1996). Spatio-temporal prediction of snow water equivalent using the Kalman filter. Computational Statistics and Data Analysis, 22, 159-175.
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    • Huang, H.1    Cressie, N.2
  • 7
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    • Multivariate geostatistical approach to space-time data analysis
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  • 8
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    • An approach to intervention analysis in spatio-temporal modelling of river quality
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    • Thas, O. and Ottoy, J.P. (1999). An approach to intervention analysis in spatio-temporal modelling of river quality. In Statistics for the Environment 4: Statistical Aspects of Health and the Environment, Barnett, V. (ed.), Wiley, Chichester, UK, pp. 221-234.
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    • Thas, O.1    Ottoy, J.P.2
  • 9
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    • Linear recursive equations, covariance selection, and path analysis
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  • 11
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    • A dimension-reduced approach to space-time Kalman filtering
    • Wikle, C. and Cressie, N (1999). A dimension-reduced approach to space-time Kalman filtering. Biometrika, 86(4), 815-829.
    • (1999) Biometrika , vol.86 , Issue.4 , pp. 815-829
    • Wikle, C.1    Cressie, N.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.