activity
20122021
most citedQuasi-Likelihood Analysis for Stochastic Regression Models with Nonsynchronous Observations

13 citations · 13 across the 2 of their papers we have counts for

collaborators
Showing math.STShow all

5 papers · 1 filter

math.ST2021

Efficient drift parameter estimation for ergodic solutions of backward SDEs

Teppei Ogihara, Mitja Stadje

We derive consistency and asymptotic normality results for quasi-maximum likelihood methods for drift parameters of ergodic stochastic processes observed in discrete time in an und…

math.ST2021

Local Asymptotic Mixed Normality via Transition Density Approximation and an Application to Ergodic Jump-Diffusion Processes

Teppei Ogihara, Yuma Uehara

We study sufficient conditions for local asymptotic mixed normality. We weaken the sufficient conditions in Theorem 1 of Jeganathan (Sankhya Ser. A 1982) so that they can be applie…

math.ST2020

Malliavin calculus techniques for local asymptotic mixed normality and their application to degenerate diffusions

Masaaki Fukasawa, Teppei Ogihara

We study sufficient conditions for a local asymptotic mixed normality property of statistical models. We develop a scheme with the regularity condition proposed by Jeganathan…

math.ST2019

Misspecified diffusion models with high-frequency observations and an application to neural networks

Teppei Ogihara

We study the asymptotic theory of misspecified models for diffusion processes with noisy nonsynchronous observations. Unlike with correctly specified models, the original maximum-l…

math.ST201213 cited

Quasi-Likelihood Analysis for Stochastic Regression Models with Nonsynchronous Observations

Teppei Ogihara, Nakahiro Yoshida

We consider nonsynchronous sampling of parameterized stochastic regression models, which contain stochastic differential equations. Constructing a quasi-likelihood function, we pro…