动态误差分解与溯源是误差理论及精度理论的逆向问题，在动态测量及动态测试系统的设计中具有十分重要的意义。
This theory is the converse issue of error and precision theory, which has very important practical meaning in dynamic measuring and the design of dynamic measuring system.
在讨论神经网络方法的基础上，尝试将其应用于动态测量误差分解理论。
Neural network method is discussed and applied to error decomposition theory of dynamic measurement.
在此基础上建立了描述上海城市竞争力短期动态变化的误差修正模型，并进行了预测方差分解。
Subsequently it establishes error correction models to describe short-term dynamic change and carries on forecast variance decomposition.
具体的实证方法是采用VAR方法，在得出协整方程下，再进一步采用误差修正、脉冲响应、方差分解等技术来探讨汇率的动态变化过程。
It adopts the var method to get the co-integrated equation, and discusses the dynamic process with the techniques such as VECM, impulse response and variance decomposition.
具体的实证方法是采用VAR方法，在得出协整方程下，再进一步采用误差修正、脉冲响应、方差分解等技术来探讨汇率的动态变化过程。
It adopts the var method to get the co-integrated equation, and discusses the dynamic process with the techniques such as VECM, impulse response and variance decomposition.
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