Jihong Park

collaborators

Showing stat.MEShow all

3 papers · 1 filter

stat.ME2026

Strong Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in $r$ -Largest Generalized Extreme-Value Models

Jihong Park, Yire Shin, Jeong-Soo Park

We study maximum likelihood estimation in the three-parameter $r$ -largest generalized extreme-value ( $r$ GEV) model with a fixed number $r$ of upper order statistics per block. Beca…

stat.ME2026

Automated selection of $r$ in $r$ -largest order statistics models: finite-sample performance and return-level inference

Yire Shin, Jihong Park, Jeong-Soo Park

Selecting the number $r$ of upper order statistics is a key practical issue in fitting $r$ -largest order statistics models. The entropy difference test for selecting $r$ relies on…

stat.ME2025

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…

Strong Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in r-Largest Generalized Extreme-Value Models

Automated selection of r in r-largest order statistics models: finite-sample performance and return-level inference

Generalized method of L-moment estimation for stationary and nonstationary extreme value models

Strong Consistency and Asymptotic Normality of the Maximum Likelihood Estimator in $r$ -Largest Generalized Extreme-Value Models

Automated selection of $r$ in $r$ -largest order statistics models: finite-sample performance and return-level inference