Why FARIMA Models are Brittle
Applications
2012-03-29 v1 Other Statistics
Abstract
The FARIMA models, which have long-range-dependence (LRD), are widely used in many areas. Through deriving a precise characterisation of the spectrum, autocovariance function, and variance time function, we show that this family is very atypical among LRD processes, being extremely close to the fractional Gaussian noise in a precise sense. Furthermore, we show that this closeness property is not robust to additive noise. We argue that the use of FARIMA, and more generally fractionally differenced time series, should be reassessed in some contexts, in particular when convergence rate under rescaling is important and noise is expected.
Cite
@article{arxiv.1203.6140,
title = {Why FARIMA Models are Brittle},
author = {Anders Gorst-Rasmussen and Darryl Veitch and András Gefferth},
journal= {arXiv preprint arXiv:1203.6140},
year = {2012}
}
Comments
20 pages, 3 figures