地震学报（英文版）
地震學報（英文版）
지진학보（영문판）
ACTA SEISMOLOGICA SINICA
2004年
5期
578-584
,共7页
韩天锡%蒋淳%魏雪丽%韩梅%冯德益
韓天錫%蔣淳%魏雪麗%韓梅%馮德益
한천석%장순%위설려%한매%풍덕익
joint multivariate statistical model%principal component analysis%discriminatory analysis%synthetic earthquake predication
Considering the problems that should be solved in the synthetic earthquake prediction at present, a new model is proposed in the paper. It is called joint multivariate statistical model combined by principal component analysis with discriminatory analysis. Principal component analysis and discriminatory analysis are very important theories in multivariate statistical analysis that has developed quickly in the late thirty years. By means of maximization information method, we choose several earthquake prediction factors whose cumulative proportions of total sample variances are beyond 90% from numerous earthquake prediction factors. The paper applies regression analysis and Mahalanobis discrimination to extrapolating synthetic prediction. Furthermore, we use this model to characterize and predict earthquakes in North China (30°～42°N, 108°～125°E) and better prediction results are obtained.
