4 papers
Sparse principal component analysis for high-dimensional stationary time series
Kou Fujimori, Yuichi Goto, Yan Liu +1
We consider the sparse principal component analysis for high-dimensional stationary processes. The standard principal component analysis performs poorly when the dimension of the p…
Moment convergence of the generalized maximum composite likelihood estimators for determinantal point processes
Kou Fujimori, Sota Sakamoto, Yasutaka Shimizu
The maximum composite likelihood estimator for parametric models of determinantal point processes (DPPs) is discussed. Since the joint intensities of these point processes are give…
Cox's proportional hazards model with a high-dimensional and sparse regression parameter
Kou Fujimori
This paper deals with the proportional hazards model proposed by D. R. Cox in a high-dimensional and sparse setting for a regression parameter. To estimate the regression parameter…
The Dantzig selector for a linear model of diffusion processes
Kou Fujimori
In this paper, a linear model of diffusion processes with unknown drift and diagonal diffusion matrices is discussed. We will consider the estimation problems for unknown parameter…