3 papers
stat.ME2025
Seamless Phase I--II Cancer Clinical Trials Using Kernel-Based Covariate Similarity
Kana Makino, Natsumi Makigusa, Masahiro Kojima
In response to the U.S.\ Food and Drug Administration's (FDA) Project Optimus, a paradigm shift is underway in the design of early-phase oncology trials. To accelerate drug develop…
math.ST2020
Two-sample test based on maximum variance discrepancy
Natsumi Makigusa
In this article, we introduce a novel discrepancy called the maximum variance discrepancy for the purpose of measuring the difference between two distributions in Hilbert spaces th…
math.ST2019
Asymptotics and practical aspects of testing normality with kernel methods
Natsumi Makigusa, Kanta Naito
This paper is concerned with testing normality in a Hilbert space based on the maximum mean discrepancy. Specifically, we discuss the behavior of the test from two standpoints: asy…