TY - JOUR
T1 - The Dantzig selector for a linear model of diffusion processes
AU - Fujimori, Kou
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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 parameters based on the discrete time observation in high-dimensional and sparse settings. To estimate drift matrices, the Dantzig selector which was proposed by Candés and Tao in 2007 will be applied. We will prove two types of consistency of the Dantzig selector for the drift matrix; one is the consistency in the sense of lq norm for every q∈ [1 , ∞] and another is the variable selection consistency. Moreover, we will construct an asymptotically normal estimator for the drift matrix by using the variable selection consistency of the Dantzig selector.
AB - 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 parameters based on the discrete time observation in high-dimensional and sparse settings. To estimate drift matrices, the Dantzig selector which was proposed by Candés and Tao in 2007 will be applied. We will prove two types of consistency of the Dantzig selector for the drift matrix; one is the consistency in the sense of lq norm for every q∈ [1 , ∞] and another is the variable selection consistency. Moreover, we will construct an asymptotically normal estimator for the drift matrix by using the variable selection consistency of the Dantzig selector.
KW - Dantzig selector
KW - Diffusion process
KW - High-dimension
KW - Sparse estimation
KW - Variable selection
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U2 - 10.1007/s11203-018-9191-y
DO - 10.1007/s11203-018-9191-y
M3 - Article
AN - SCOPUS:85054577863
SN - 1387-0874
JO - Statistical Inference for Stochastic Processes
JF - Statistical Inference for Stochastic Processes
ER -