dc.contributor.author |
Edwards, M |
en |
dc.contributor.author |
Meyer, Renate |
en |
dc.contributor.author |
Christensen, NL |
en |
dc.coverage.spatial |
Auckland University of Technology |
en |
dc.date.accessioned |
2017-04-12T00:08:33Z |
en |
dc.date.issued |
2016-11-28 |
en |
dc.identifier.citation |
2016 Joint NZSA and ORSNZ Conference |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/32571 |
en |
dc.description.abstract |
We present a new Bayesian nonparametric approach to estimating the spectral density of a stationary time series. A nonparametric prior based on a mixture of B-spline distributions is speci ed and can be regarded as a generalization of the Bernstein polynomial prior of Petrone (1999a,b) and Choudhuri et al. (2004). Whittle's likelihood approximation is used to obtain the pseudo-posterior distribution. This method allows for a data-driven choice of the smoothing parameter as well as the number and the location of the knots. Posterior samples are obtained using a parallel tempered Metropolis-within-Gibbs Markov chain Monte Carlo algorithm. We conduct a simulation study to demonstrate that under default noninformative priors, the B-spline prior provides more accurate Monte Carlo estimates in terms of L1-error and uniform coverage probabilities than the Bernstein polynomial prior. Finally, we demonstrate the algorithm's ability to estimate a spectral density with sharp features, using real gravitational wave detector data from LIGO's sixth science run, recoloured to match the Advanced LIGO target sensitivity. |
en |
dc.relation.ispartof |
2016 Joint NZSA and ORSNZ Conference |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.title |
Bayesian nonparametric spectral density estimation using B-spline priors |
en |
dc.type |
Presentation |
en |
pubs.author-url |
http://orsnz.org.nz/conf50/wp-content/uploads/sites/2/2016/11/2016-Joint-NZSAORSNZ-Abstract-Booklet.pdf |
en |
pubs.finish-date |
2016-11-30 |
en |
pubs.start-date |
2016-11-26 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Conference Oral Presentation |
en |
pubs.elements-id |
606123 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Statistics |
en |
pubs.record-created-at-source-date |
2017-01-12 |
en |