Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models
We discuss computational aspects of likelihood-based estimation of univariate ARFIMA (p,d,q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.
|Date of creation:||29 Nov 2001|
|Date of revision:|
|Contact details of provider:|| Web page: https://www.nuffield.ox.ac.uk/economics/|
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