论文标题
在Ornstein-uhlenbeck噪声下的多项式和随机Hodgkin-Huxley Systems的推断
Polynomials under Ornstein-Uhlenbeck noise and an application to inference in stochastic Hodgkin-Huxley systems
论文作者
论文摘要
我们讨论了估计问题，在长期间隔内观察到多项式的估计问题。我们证明局部渐近正态性（LAN）并指定渐近有效的估计器。我们将其应用于以下问题：将噪声馈送到神经科学的经典（确定性）Hodgkin Huxley模型中，我们对噪声过程参数的渐近有效估计感兴趣。
We discuss estimation problems where a polynomial is observed under Ornstein Uhlenbeck noise over a long time interval. We prove local asymptotic normality (LAN) and specify asymptotically efficient estimators. We apply this to the following problem: feeding noise into the classical (deterministic) Hodgkin Huxley model of neuroscience, we are interested in asymptotically efficient estimation of the parameters of the noise process.
