地震学报（英文版）2004，Vol.17Issue(5)：578-584,7.
Joint multivariate statistical model and its applications to the synthetic earthquake prediction
Joint multivariate statistical model and its applications to the synthetic earthquake prediction
摘要
Abstract
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.关键词
joint multivariate statistical model/principal component analysis/discriminatory analysis/synthetic earthquake predicationKey words
joint multivariate statistical model/principal component analysis/discriminatory analysis/synthetic earthquake predication分类
天文与地球科学引用本文复制引用
韩天锡,蒋淳,魏雪丽,韩梅,冯德益..Joint multivariate statistical model and its applications to the synthetic earthquake prediction[J].地震学报（英文版）,2004,17(5):578-584,7.基金项目
Key Project of the Tenth Five-year Plan of State Scientific Commission (2001BA601B01-010506). （2001BA601B01-010506）
