在僅能觀測到部分資料的情形下,ODE model的參數估計
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2013
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Abstract
在物理、化學、生物的領域上,我們常常會用微分方程模型去描述自然的現象。而對於這樣一個微分方程模型,我們可能僅能觀測到裡面的其中某幾個參數。在這樣的情形底下,我們該如何去做微分方程模型的參數估計?這就是我們要討論的議題。在考慮到電腦計算的速度以及參數估計的精確度,本文以Hindmarsh-Rose Type model做為例子,提供了一套參數估計的方法。
In physics, chemistry and biology, many researcher try to describe natural phenomena by ordinary differential equations (ODE) due to the fact that a lot of elegant theorem can be found in ODE and its nonlinear properties. With the observed information and some prior knowledge for a potential model, parameter estimation of an ODE model often requires a lot of computation works, such as a numerical integration of the ODE system and minimization of the log-likelihood function. In this paper, we consider a partially observed ODE model: 2D-HR type model. With the partially information, we present a simple way (iterative estimation process) without too mach computation to estimate the parameters in this model.
In physics, chemistry and biology, many researcher try to describe natural phenomena by ordinary differential equations (ODE) due to the fact that a lot of elegant theorem can be found in ODE and its nonlinear properties. With the observed information and some prior knowledge for a potential model, parameter estimation of an ODE model often requires a lot of computation works, such as a numerical integration of the ODE system and minimization of the log-likelihood function. In this paper, we consider a partially observed ODE model: 2D-HR type model. With the partially information, we present a simple way (iterative estimation process) without too mach computation to estimate the parameters in this model.
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參數估計, 微分方程模型, 類Hindmarsh-Rose模型, parameter estimation, ordinary differential equations, Hindmarsh-Rose Type model, partially observed model