Abrupt change point detection of annual maximum precipitation using fused lasso
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- 作者：Jong-June Jeona ; Jang Hyun Sungb ; Eun-Sung Chungc ; eschung@seoultech.ac.kr" class="auth_mail" title="E-mail the corresponding author
- 关键词：Annual maximum precipitation ; Bayesian change point analysis ; Fused lasso penalty ; GEV distribution ; Skewness
- 刊名：Journal of Hydrology
- 出版年：2016
- 出版时间：July 2016
- 年：2016
- 卷：538
- 期：Complete
- 页码：831-841
- 全文大小：1806 K
文摘
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This study proposed the fused lasso penalty function to detect the change point of AMP, which can generally be fitted using the GEV distribution.
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Four numerical experiments and the real data application for 63 weather stations are conducted to compare the detection performance between BCPA and the fused lasso method.
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The GEV fused lasso method detects the change points of the non-stationary AMPs of South Korea because the means of AMPs didn’t go back to their previous values after the change point.