AR(∞)估计与非参数随机复杂性

L. Gerencsér
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引用次数: 0

摘要

设H*为线性随机系统的传递函数,使得H*及其逆在H∞(D)中。将系统写成AR(∞)系统,使用最小二乘法估计系统的最佳AR(k)近似值。然后研究了欠建模和参数不确定性(由于估计)对预测的影响,以及k的最优选择。结果应用于arma系统的AR逼近。
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AR( infinity ) estimation and nonparametric stochastic complexity
Let H* be the transfer function of a linear stochastic system such that H* and its inverse are in H infinity (D). Writing the system as an AR( infinity ) system, the best AR(k) approximation of the system is estimated using the method of least squares. Then the effect of undermodeling and parameter uncertainty (due to estimation) on prediction, and the optimal choice of k are investigated. The result is applied to the AR approximation of ARMA-systems.<>
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