Statistical modelling for multivariate models of high dimension

Research Project

Project/Area Number	25K16617
Research Category	Grant-in-Aid for Early-Career Scientists
Allocation Type	Multi-year Fund
Review Section	Basic Section 07030:Economic statistics-related
Research Institution	Keio University
Principal Investigator	POIGNARD BENJAMIN 慶應義塾大学, 理工学部(矢上), 准教授 (40845252)
Project Period (FY)	2025-04-01 – 2028-03-31
Project Status	Granted (Fiscal Year 2025)
Budget Amount *help	¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000) Fiscal Year 2027: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000) Fiscal Year 2026: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000) Fiscal Year 2025: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Keywords	Asymptotic theory / High dimension / M-estimator / Sparsity
Outline of Research at the Start	The research will be dedicated to the development of novel statistical methods for multivariate models to best fit the observed patterns while solving the curse of dimensionality. We will specify suitable penalization methods to capture the features of the data (e.g., sparsity and/or changepoints).