DERIVING THE EXACT DISCRETE ANALOG OF A CONTINUOUS TIME SYSTEM
提出一种方法，从线性随机微分方程系统生成的等距数据中推导出精确离散模型，该方法不限制观测数据的性质，并展示了如何将离散模型表示为渐近时不变向量自回归移动平均模型。
The exact discrete model satisfied by equispaced data generated by a linear stochastic differential equations system is derived by a method that does not imply restrictions on observed discrete data per se. The method involves integrating the solution of the continuous time model in state space form and a nonstandard change in the order of three types of integration, facilitating the representation of the exact discrete model as an asymptotically time-invariant vector autoregressive moving average model. The method applying to the state space form is general and is illustrated using the prototypical higher order model for mixed stock and flow data discussed by Bergstrom (1986, Econometric Theory 2, 350–373).