4 papers
Debiased and Simultaneous Inference for Heterogeneous Factorial Effect Modifiers via Residualized Walsh-Hadamard Scores
Tomoshige Nakamura, Ryo Emoto
In factorial randomized experiments with binary treatment components, we study which baseline covariates modify component main effects and interactions. We define effect-modifi…
Selective Inference for CART with Binary Outcomes
Tomoshige Nakamura
Binary classification trees select subgroups using the same outcomes later used to assess their differences. We develop finite-sample conditional tests of a common success probabil…
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…
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…