7 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
Selective Inference in Propensity Score Analysis
Yoshiyuki Ninomiya, Yuta Umezu, Ichiro Takeuchi
Selective inference (post-selection inference) is a methodology that has attracted much attention in recent years in the fields of statistics and machine learning. Naive inference…
Selective Inference via Marginal Screening for High Dimensional Classification
Yuta Umezu, Ichiro Takeuchi
Post-selection inference is a statistical technique for determining salient variables after model or variable selection. Recently, selective inference, a kind of post-selection inf…
On the Consistency of the Bias Correction Term of the AIC for the Non-Concave Penalized Likelihood Method
Yuta Umezu, Yoshiyuki Ninomiya
Penalized likelihood methods with an -type penalty, such as the Bridge, the SCAD, and the MCP, allow us to estimate a parameter and to do variable selection, simultaneously…
AIC for Non-concave Penalized Likelihood Method
Yuta Umezu, Yusuke Shimizu, Hiroki Masuda +1
Non-concave penalized maximum likelihood methods, such as the Bridge, the SCAD, and the MCP, are widely used because they not only do parameter estimation and variable selection si…