AJCM  Vol.3 No.3 B , September 2013
Hierarchical Linear Model of Monthly Rainfall with Regional and Seasonal Interaction Effects

According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.

Cite this paper: Y. Zhu, H. Lu and Z. Zhu, "Hierarchical Linear Model of Monthly Rainfall with Regional and Seasonal Interaction Effects," American Journal of Computational Mathematics, Vol. 3 No. 3, 2013, pp. 1-6. doi: 10.4236/ajcm.2013.33B001.

[1]   Y. H. Zhu and G. X. Jiang, “Hierarchical Linear Model and Its Research on Hierarchical Characteristics of Rainfall,” 2011 International Conference on Multimedia Technology (ICMT 2011), pp. 2146-2150.

[2]   S. W. Raudenbush, A. S. Bryk and Z. G. Guo, “Hierarchical Linear Models: Application and Data Analysis Method,” Beijing: Social Sciences Academic Press, 2007, pp. 83-90.

[3]   J. C. Wang, H. Y. Xie and B. F. Jiang, “Application of Hierarchical Linear Model——Methods and Applications,” Beijing: Higher Education Press, 2007, pp. 27-30.

[4]   L. Zhang, L. Lei and B. L. Guo, “Application of Hierarchical Linear Model,” Beijing: Science and Education Press, 2003, pp. 28-40.

[5]   X. Zhang and J. Y. Wang, “The Study for the Sample Size Problem about Hierarchical Linear Models,” Statistics and Decision, Vol. 15, 2010, pp. 4-8.