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math.ST2026
High-dimensional linear regression inference via weak convergence
Kou Fujimori, Koji Tsukuda
We prove weak convergence in a separable Hilbert space for estimators of high-dimensional regression coefficients, which yields asymptotic normality and enables direct use of stand…
math.ST2024
Two step estimations via the Dantzig selector for models of stochastic processes with high-dimensional parameters
Kou Fujimori, Koji Tsukuda
We consider the sparse estimation for stochastic processes with possibly infinite-dimensional nuisance parameters, by using the Dantzig selector which is a sparse estimation method…