论文标题
SPDE模型中的参数估计用于细胞重极化
Parameter Estimation in an SPDE Model for Cell Repolarisation
论文作者
论文摘要
作为一种混凝土设置，随机部分微分方程（SPDE）能够对真实现象进行建模，我们提出了一个随机的Meinhardt模型，用于细胞重呈极化，并研究如何针对简单线性SPDE模型开发的参数估计技术在这种情况下应用。我们建立了温和的SPDE溶液的存在，并研究了驱动噪声过程对溶液中模式形成的影响。然后，随着空间分辨率变得更细，我们追求扩散项的估计，并显示估计值的渐近正态性。研究有限样本性能以获取合成和真实数据。
As a concrete setting where stochastic partial differential equations (SPDEs) are able to model real phenomena, we propose a stochastic Meinhardt model for cell repolarisation and study how parameter estimation techniques developed for simple linear SPDE models apply in this situation. We establish the existence of mild SPDE solutions and we investigate the impact of the driving noise process on pattern formation in the solution. We then pursue estimation of the diffusion term and show asymptotic normality for our estimator as the space resolution becomes finer. The finite sample performance is investigated for synthetic and real data.
