An improved ARIMA model for precipitation simulations

Nonlinear Processes in Geophysics

Volumn 21, Issue 6, 2014, Pages 1159-1168

  Wang, H R ^a   Wang, C ^a   Lin, X ^a   Kang, J ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ANNUAL VARIATION; CLUSTER ANALYSIS; MODELING; PRECIPITATION ASSESSMENT; TIME SERIES;

CHINA; GANSU; LANZHOU;

EID: 84914672484     PISSN: 10235809     EISSN: 16077946     Source Type: Journal    
DOI: 10.5194/npg-21-1159-2014     Document Type: Article

References (19)

1. Ahmad, S., Khan, I. H., and Parida, B. P.: Performance of stochastic approaches for forecasting river water quality, Water Res., 35, 4261-4266, 2001.
2. Box, G. E. P.: Models for forecasting seasonal and nonseasonal time series, in: Spectral Analysis of Time Series, edited by: Harris, B., Wiley, New York, 271-311, 1967.
3. Box, G. E. P.: Time Series Analysis Forecasting And Control, China Statistics Press, Beijing, China, 1997.
4. Ip, W. C., Wong, H., and Wang, S. G.: A GIC rule for assessing data transformation in regression, Statist. Probab. Lett., 68, 105-110, 2004.
5. Jin, J. L., Ding, J., and Wei, Y. M.: Threshold autoregressive model based on genetic algorithm and its application to forecasting the shallow groundwater level, Hydraul. Eng., 27, 51-55, 1999.
6. Kohn, R.: Estimation, prediction, and interpolation for ARIMA models with missing data, J. Am. Stat. Assoc., 81, 751-761, 1986.
7. Lehmann, A. and Rode, M.: Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany, Water Res., 35, 2153-2160, 2001.
8. Mcleod, A. I. and Sales, P. R. H.: An algorithm for approximate likelihood calculation of ARMA and seasonal ARMA models, Appl. Stat., 32, 211-223, 1983.
9. Melard, G.: A fast algorithm for the exact likelihood of autoregressive-moving average models, Appl. Stat., 33, 104-119, 1984.
10. Meloun, M., Sáňka, M., and Němec, P.: The analysis of soil cores polluted with certain metals using the Box-Cox transformation, Environ. Pollut., 137, 273-280, 2005.
11. Niua, X. F., Edmiston, H. L., and Bailey, G. O.: Time series models for salinity and other environmental factors in the Apalachicola estuarine system. Estuarine, Coast. Shelf Sci., 46, 549-563, 1998.
12. Pankratz, A.: Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, Wiley, New York, 1983.
13. Qi, W. and Zhen, M. P.: Winters and ARIMA model analysis of the lake level of salt Lake Zabuye, Tibetan Plateau, J. Lake Sci., 18, 21-28, 2006.
14. Shumway, R. H. and Stoffer, D. S.: Time Series Analysis and Its Applications Springer-Verlag New York, Inc., Secaucus, NJ, USA, 2005.
15. Sun, L. H., Zhao, Z. G., and Xu, L.: Study of summer rain pattern in monsoon region of east China and its circulation cause, J. Appl. Meteorol. Sci., 16, 57-62, 2005.
16. Thyer, M., Kuczera, G., and Wang, Q. J.: Quantifying parameter uncertainty in stochastic models using the Box-Cox transformation, J. Hydrol., 265, 246-257, 2002.
17. Toth, E. A. and Montanari, B. A.: Real-time flood forecasting via combined use of conceptual and stochastic models, Phys. Chem. Earth B, 24, 793-798, 1999.
18. Wang, H. R., Ye, L. T., and Liu, C. M.: Problems in wavelet analysis of hydrologic series and some suggestions on improvement, Prog. Nat. Sci., 17, 80-86, 2007.
19. Wang, Y., Yin, L. Z., and Zhang, Y.: Judging model of fuzzy optimal dividing based on improved objective function clustering method, Math. Pract. Theory, 35, 142-147, 2005.