5 citations · 9 across the 12 of their papers we have counts for
12 papers
Structural grouping of extreme value models via graph fused lasso
Takuma Yoshida, Koki Momoki, Shuichi Kawano
The generalized Pareto distribution (GPD) is a fundamental model for analyzing the tail behavior of a distribution. In particular, the shape parameter of the GPD characterizes the…
Small area estimation of dependent extreme value indices
Koki Momoki, Takuma Yoshida
In extreme value analysis, tail behavior of a heavy-tailed data distribution is modeled by a Pareto-type distribution in which the so-called extreme value index (EVI) controls the…
Sure independence screening for covariate-dependent extreme value index estimation
Takuma Yoshida, Yuta Umezu
One of the main topics in extreme value analysis is the estimation of the extreme value index, which characterizes the tail behavior of a distribution. Although covariate dependent…
Mixed effects models for extreme value index regression
Koki Momoki, Takuma Yoshida
Extreme value theory (EVT) provides an elegant mathematical tool for the statistical analysis of rare events. When data are collected from multiple population subgroups, because so…
Asymptotic theory for extreme value generalized additive models
Takuma Yoshida
The classical approach to analyzing extreme value data is the generalized Pareto distribution (GPD). When the GPD is used to explain a target variable with the large dimension of c…
Hypothesis testing for varying coefficient models in tail index regression
Koki Momoki, Takuma Yoshida
This study examines the varying coefficient model in tail index regression. The varying coefficient model is an efficient semiparametric model that avoids the curse of dimensionali…