部分和离散观测下遍历线性偏微分方程的参数估计
Parameter estimation for ergodic linear SDEs from partial and discrete observations
摘要:
考虑线性随机微分方程描述的状态空间模型的参数估计问题。我们假设一个不可观测的Ornstein-Uhlenbeck过程通过线性随机微分方程驱动另一个可观测的过程,并且这两个过程依赖于一些未知参数.我们构造了未知参数的拟似然估计(QMLE),并证明了该估计的渐近性质。
英文摘要:
We consider a problem of parameter estimation for the state space model described by linear stochastic differential equations. We assume that an unobservable Ornstein-Uhlenbeck process drives another observable process by the linear stochastic differential equation, and these two processes depend on some unknown parameters. We construct the quasi-likelihood estimator (QMLE) of the unknown parameters and show asymptotic properties of the estimator.
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