Open AccessPENENTUAN NILAI AMBANG BATAS SEBARAN PARETO TERAMPAT DENGAN MEASURE OF SURPRISE
Author(s) -
Yumna Karimah,
Aji Hamim Wigena,
Agus Mohamad Soleh
Publication year - 2019
Publication title -
indonesian journal of statistics and applications
Language(s) - English
Resource type - Journals
ISSN - 2599-0802
DOI - 10.29244/ijsa.v3i2.284
Subject(s) - generalized pareto distribution , extreme value theory , pareto principle , measure (data warehouse) , surprise , generalized extreme value distribution , natural disaster , statistics , landslide , environmental science , residual , pareto distribution , mathematics , meteorology , computer science , geography , geology , data mining , algorithm , psychology , social psychology , geotechnical engineering
Extreme rainfall can result in natural disasters such as floods and landslides. These natural disasters will cause damage and losses to the surrounding environment. Prevention of damage from natural disasters can be done by extreme rainfall estimation. Estimates of extreme rainfall are based on Generalized Pareto Distribution (GPD) which requires threshold value information. The threshold value can be determined by two methods, namely Mean Residual Life Plot (MRLP) and Measure of Surprise (MOS). The purpose of this study is to determine and compare the threshold values of MRLP and MOS. The data used are 10-day and monthly rainfall data. The results of this study indicate that the procedure of MOS is shorter and easier than that of MRLP. Based on the cross validation result, the log-likelihood value of MOS is larger than that of MRLP, then MOS is better than MRLP.