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pro vyhledávání: '"Ogihara, Teppei"'
Autor:
Ogihara, Teppei
We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonrandom and observation occurs in nonsynchronous manner. The problem of nonsynchronous observations is important when we consider the analysis of high-fre
Externí odkaz:
http://arxiv.org/abs/2207.00180
Autor:
Ogihara, Teppei, Stadje, Mitja
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 underlying continuous-time setting. The special feature of our analysis i
Externí odkaz:
http://arxiv.org/abs/2109.08415
Autor:
Ogihara, Teppei, Uehara, Yuma
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 applied to a wider class of statistical models including a jump-diffusion mo
Externí odkaz:
http://arxiv.org/abs/2105.00284
Autor:
Fukasawa, Masaaki, Ogihara, Teppei
We study sufficient conditions for a local asymptotic mixed normality property of statistical models. We develop a scheme with the $L^2$ regularity condition proposed by Jeganathan [\textit{Sankhya Ser. A} \textbf{44} (1982) 173--212] so that it is a
Externí odkaz:
http://arxiv.org/abs/2005.14599
Misspecified diffusion models with high-frequency observations and an application to neural networks
Autor:
Ogihara, Teppei
We study the asymptotic theory of misspecified models for diffusion processes with noisy nonsynchronous observations. Unlike with correctly specified models, the original maximum-likelihood-type estimator has an asymptotic bias under the misspecified
Externí odkaz:
http://arxiv.org/abs/1912.11832
Akademický článek
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Misspecified diffusion models with high-frequency observations and an application to neural networks
Autor:
Ogihara, Teppei
Publikováno v:
In Stochastic Processes and their Applications December 2021 142:245-292
Autor:
Ogihara, Teppei1 (AUTHOR) ogihara@mist.i.u-tokyo.ac.jp, Stadje, Mitja2 (AUTHOR)
Publikováno v:
Scandinavian Journal of Statistics. Sep2024, Vol. 51 Issue 3, p1181-1205. 25p.
Autor:
Ogihara, Teppei, Yoshida, Nakahiro
We introduce a point process regression model that is applicable to price models and limit order book models. Hawkes type autoregression in the intensity process is generalized to a stochastic regression to covariate processes. We establish the so-ca
Externí odkaz:
http://arxiv.org/abs/1512.01619
Autor:
Ogihara, Teppei, Tanaka, Hideyuki
We deduce the asymptotic error distribution of the Euler method for the nonlinear filtering problem with continuous-time observations. Previous works by several authors have shown that the error structure of the method is characterized by conditional
Externí odkaz:
http://arxiv.org/abs/1511.06520