9 papers
Network inference for SDEs with diverging dimension under small noise
Francesco Iafrate, Nakahiro Yoshida, Stefano M. Iacus
We consider inference for network stochastic differential equations in a small-noise, high-dimensional regime, where the diffusion coefficient vanishes with $\ep\to0$ while the net…
Risk comparison theorems and application to deep learning of diffusion coefficients
Arnaud Gloter, Nakahiro Yoshida
We investigate the nonparametric estimation of the diffusion matrix in stochastic differential equations featuring multidimensional, strong mixing covariate processes. We propose a…
Drift estimation for rough processes under small noise asymptotic : QMLE approach
Arnaud Gloter, Nakahiro Yoshida
We consider a process $X^\ve$ solution of a stochastic Volterra equation with an unknown parameter in the drift function. The Volterra kernel is singular near zero, exhib…
Deep learning of point processes for modeling high-frequency data
Yoshihiro Gyotoku, Ioane Muni Toke, Nakahiro Yoshida
We investigate applications of deep neural networks to a point process having an intensity with mixing covariates processes as input. Our generic model includes Cox-type models and…
Drift estimation for rough processes under small noise asymptotic : trajectory fitting method
Arnaud Gloter, Nakahiro Yoshida
We consider a process $X^\ve$ that solves a stochastic Volterra equation with an unknown parameter in the drift function. The Volterra kernel is singular, and includes as…
Statistical inference for highly correlated stationary point processes and noisy bivariate Neyman-Scott processes
Takaaki Shiotani, Nakahiro Yoshida
Motivated by estimating the lead-lag relationships in high-frequency financial data, we propose noisy bivariate Neyman-Scott point processes with gamma kernels (NBNSP-G). NBNSP-G t…
Asymptotic expansion of the drift estimator for the fractional Ornstein-Uhlenbeck process
Ciprian A. Tudor, Nakahiro Yoshida
We present an asymptotic expansion formula of an estimator for the drift coefficient of the fractional Ornstein-Uhlenbeck process. As the machinery, we apply the general expansion…
Log-rank test with coarsened exact matching
Tomoya Baba, Nakahiro Yoshida
It is of special importance in the clinical trial to compare survival times between the treatment group and the control group. Propensity score methods with a logistic regression m…
Quasi-likelihood analysis for adaptive estimation of a degenerate diffusion process
Arnaud Gloter, Nakahiro Yoshida
The adaptive quasi-likelihood analysis is developed for a degenerate diffusion process. Asymptotic normality and moment convergence are proved for the quasi-maximum likelihood esti…