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1. 4. 2010.
Fast Computation of the Kullback–Leibler Divergence and Exact Fisher Information for the First-Order Moving Average Model
In this note expressions are derived that allow computation of the Kullback-Leibler (K-L) divergence between two first-order Gaussian moving average models in O n(1) time as the sample size n ¿ ¿. These expressions can also be used to evaluate the exact Fisher information matrix in On(1) time, and provide a basis for an asymptotic expression of the K-L divergence.