论文标题
稀疏添加剂普通微分方程的联合估计方法
A Joint Estimation Approach to Sparse Additive Ordinary Differential Equations
论文作者
论文摘要
普通的微分方程（ODE）被广泛用于表征实际应用中复杂系统的动力学。在本文中，我们提出了一种新型的联合估计方法，用于允许观测值是非高斯的广义稀疏添加剂。通过同时考虑可能性，ode保真度和稀疏正则化，将新方法与现有搭配方法统一。我们设计了一个块坐标下降算法，以优化非凸和非差异目标函数。建立了算法的全球融合。模拟研究和两种应用表明，在估计稀疏结构的估计中，提出的方法的出色表现。
Ordinary differential equations (ODEs) are widely used to characterize the dynamics of complex systems in real applications. In this article, we propose a novel joint estimation approach for generalized sparse additive ODEs where observations are allowed to be non-Gaussian. The new method is unified with existing collocation methods by considering the likelihood, ODE fidelity and sparse regularization simultaneously. We design a block coordinate descent algorithm for optimizing the non-convex and non-differentiable objective function. The global convergence of the algorithm is established. The simulation study and two applications demonstrate the superior performance of the proposed method in estimation and improved performance of identifying the sparse structure.
