3 papers
stat.ME2026
Robust estimation via -divergence for diffusion processes
Tomoyuki Nakagawa, Yusuke Shimizu
This paper deals with the problem of outliers in high frequency observation data from diffusion processes. Robust estimation methods are needed because the inclusion of outliers ca…
stat.ME2016
On the Consistency of the Bias Correction Term of the AIC for the Non-Concave Penalized Likelihood Method
Yuta Umezu, Yoshiyuki Ninomiya
Penalized likelihood methods with an -type penalty, such as the Bridge, the SCAD, and the MCP, allow us to estimate a parameter and to do variable selection, simultaneously…
math.ST2015
Update estimation of diffusion parameter observed at high frequency
Yusuke Shimizu
We propose an update estimation method for a diffusion parameter from high-frequency dependent data under a nuisance drift element. We ensure the asymptotic equivalence of the esti…