MASUDA Hiroki

MASUDA Hiroki is a professor at the Graduate School of Mathematical Sciences, The University of Tokyo. His research interests include statistical analyses for stochastic process models, with a focus on statistical modeling based on non-Gaussian stochastic processes and their implementation. His current research involves studying model assessments and multivariate analyses based on the distributional approximation of functionals of Lévy processes, as well as limit theorems related to developing statistical methodologies. He has published extensively in areas such as ergodicity, exponential beta-mixing bounds, and quasi-likelihood estimation for stochastic processes.

Hiroki Masuda is a researcher at the University of Tokyo, specializing in statistics for stochastic processes and their applications. His work focuses on the analysis of stochastic differential equations (SDEs), particularly those driven by Lévy processes, including Ornstein-Uhlenbeck processes and tempered stable processes. He has contributed to the development of computational frameworks for simulation and inference of SDEs, such as the yuima project. His research also addresses estimation methods for discretely observed processes, including quasi-likelihood estimation and model comparison techniques. Masuda's publications explore topics such as ergodicity, β-mixing bounds, and local asymptotic normality for Lévy-driven models.