23 citations · 30 across the 5 of their papers we have counts for
7 papers
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…
Fisher Information and Differentiability for -Largest Generalized Extreme-Value Models
Jihong Park, Yire Shin, Jeong-Soo Park
The largest observations of a block form a dependent random vector whose support moves with all three parameters of the -largest generalized extreme-value (GEV) model. Fo…
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…
Generalized logistic model for largest order statistics, with hydrological application
Yire Shin, Jeong-Soo Park
The effective use of available information in extreme value analysis is critical because extreme values are scarce. Thus, using the largest order statistics (rLOS) instead of t…
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…