5 papers
Asymptotic Theory and Phase Transitions for Variable Importance in Quantile Regression Forests
Tomoshige Nakamura, Hiroshi Shiraishi
Quantile Regression Forests (QRF) are widely used for non-parametric conditional quantile estimation, yet statistical inference for variable importance measures remains challenging…
Local Fr'echet Regression via RKHS embedding and Its Applications to Data Analysis on Manifolds
Yuki Iida, Hiroshi Shiraishi, Hiroaki Ogata
Local Fr'echet Regression (LFR) is a nonparametric regression method for settings in which the explanatory variable lies in a Euclidean space and the response variable lies in a me…
Time series quantile regression using random forests
Hiroshi Shiraishi, Tomoshige Nakamura, Ryotato Shibuki
We discuss an application of Generalized Random Forests (GRF) proposed by Athey et al.(2019) to quantile regression for time series data. We extracted the theoretical results of th…
Semiparametric Estimation of Optimal Dividend Barrier for Spectrally Negative Lévy Process
Yasutaka Shimizu, Hiroshi Shiraishi
We disucss a statistical estimation problem of an optimal dividend barrier when the surplus process follows a Lévy insurance risk process. The optimal dividend barrier is defined a…
M-Estimation based on quasi-processes from discrete samples of Levy processes
Yasutaka Shimizu, Hiroshi Shiraishi
We propose a novel estimation framework for path-dependent functionals of Levy processes from discretely observed data. Traditional approaches rely on Monte Carlo simulation of ful…