Parametric estimation for a parabolic linear SPDE model based on discrete observations

Kaino Yusuke; Uchida Masayuki

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Parametric estimation for a parabolic linear SPDE model based on discrete observations

机译：基于离散观测的抛物线线性SPDE模型的参数估计

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摘要

We consider parametric estimation for a parabolic linear second order stochastic partial differential equation (SPDE) from high frequency data which are observed in time and space. By using thinned data obtained from the high frequency data, adaptive estimators of the coefficient parameters including the volatility parameter are proposed. Moreover, we give some examples and simulation results of the adaptive estimators of the SPDE model based on the high frequency data. (C) 2020 Elsevier B.V. All rights reserved.

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《European Journal of Medicinal Chemistry: Chimie Therapeutique》 |2021年第1期|共31页
作者
Kaino Yusuke; Uchida Masayuki;
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作者单位

Osaka Univ Grad Sch Engn Sci Suita Osaka Japan;

Osaka Univ Grad Sch Engn Sci Suita Osaka Japan;

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原文格式 PDF
正文语种 eng
中图分类药学;
关键词
Adaptive estimation; Diffusion process; High frequency data; Stochastic partial differential equation; Thinned data;

机译：自适应估计;扩散过程;高频数据;随机偏微分方程;精简数据;

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4. Parametric estimation for a parabolic linear SPDE model based on discrete observations [J] . Kaino Yusuke, Uchida Masayuki Journal of Statistical Planning and Inference . 2021,第1期

机译：基于离散观测的抛物线线性SPDE模型的参数估计
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Parametric estimation for a parabolic linear SPDE model based on discrete observations

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