Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory processes

Craigmile, P.F. (2003) Simulating a class of stationary Gaussian processes using the Davies-Harte algorithm, with application to long memory processes. Journal of Time Series Analysis, 24(5), pp. 505-511. (doi:10.1111/1467-9892.00318)

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Abstract

We demonstrate that the fast and exact Davies–Harte algorithm is valid for simulating a certain class of stationary Gaussian processes – those with a negative autocovariance sequence for all non-zero lags. The result applies to well known classes of long memory processes: Gaussian fractionally differenced (FD) processes, fractional Gaussian noise (fGn) and the nonstationary fractional Brownian Motion (fBm).

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Craigmile, Dr Peter
Authors: Craigmile, P.F.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of Time Series Analysis
ISSN:0143-9782
ISSN (Online):1467-9892
Published Online:26 September 2003

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