From the 1 of 6 linked papers with an AI index.
6 papers
Sure independence screening for covariate-dependent extreme value index estimation
Takuma Yoshida, Yuta Umezu
The paper introduces a sure independence screening technique for estimating a covariate‑dependent extreme value index in high‑dimensional settings, using a kernel‑based conditional…
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…
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…
Single-index models for extreme value index regression
Takuma Yoshida
Since the extreme value index (EVI) controls the tail behaviour of the distribution function, the estimation of EVI is a very important topic in extreme value theory. Recent develo…
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…