Regularised estimators for ARFIMA processes
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Stochastic processes with long-range dependence are found in many applications. ARFIMA models can be used to characterise both their short-term correlations and the phenomenon of long-range dependence. Maximum likelihood estimates of the model parameters have nice statistical properties but are ill-conditioned and hard to compute. Whittle's approximation has the same asymptotic properties and yet is easier to compute. We propose a regularisation of Whittle's approximation that overcomes the problem of ill-conditioning. Good results are demonstrated in numerical simulations
| Original language | Unknown |
|---|---|
| Pages (from-to) | 298-303 |
| Number of pages | 6 |
| Journal | IFAC Proceedings Volumes (IFAC-PapersOnline) |
| Volume | 45 |
| Issue number | 16 |
| Early online date | 17 Jul 2012 |
| DOIs | |
| Publication status | Published - 21 Apr 2016 |
| Externally published | Yes |