23 citations · 30 across the 5 of their papers we have counts for
5 papers · 1 filter
Strong Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in -Largest Generalized Extreme-Value Models
Jihong Park, Yire Shin, Jeong-Soo Park
We study maximum likelihood estimation in the three-parameter -largest generalized extreme-value (GEV) model with a fixed number of upper order statistics per block. Beca…
Automated selection of in -largest order statistics models: finite-sample performance and return-level inference
Yire Shin, Jihong Park, Jeong-Soo Park
Selecting the number of upper order statistics is a key practical issue in fitting -largest order statistics models. The entropy difference test for selecting relies on…
Generalized method of L-moment estimation for stationary and nonstationary extreme value models
Yonggwan Shin, Yire Shin, Jihong Park +1
Precisely estimating out-of-sample upper quantiles is very important in risk assessment and in engineering practice for structural design to prevent a greater disaster. For this pu…
Building nonstationary extreme value model using L-moments
Yire Shin, Yonggwan Shin, Jeong-Soo Park
The maximum likelihood estimation for a time-dependent nonstationary (NS) extreme value model is often too sensitive to influential observations, such as large values toward the en…
Modeling climate extremes using the four-parameter kappa distribution for -largest order statistics
Yire Shin, Jeong-Soo Park
Accurate estimation of the T-year return levels of climate extremes using statistical distribution is a critical step in the projection of future climate and in engineering design…