dc.contributor.author | Gao, Junqiu | |
dc.date.accessioned | 2019-08-30T11:12:11Z | |
dc.date.available | 2019-08-30T11:12:11Z | |
dc.date.issued | 2019-08-30T11:12:11Z | |
dc.identifier.uri | http://hdl.handle.net/10222/76362 | |
dc.description.abstract | The Ornstein–Uhlenbeck (OU) process is a widely used model for stochastic processes, where the value drifts towards a fixed stable value. We examine how well the OU process fits the data by using likelihood ratio tests to compare models of temporal dynamics of OTUs. Then, we derive the Fisher information of the OU process and show how it can be used to maximize the temporal efficiency of sampling. We apply this to parameters estimated from real data to determine optimal sampling schemes for human microbiomes. We use simulations to show that the asymptotic theory applies to typical finite sample cases. | en_US |
dc.language.iso | en | en_US |
dc.subject | ORNSTEIN-UHLENBECK PROCESS | en_US |
dc.subject | OPTIMAL SAMPLING | en_US |
dc.subject | MICROBIOME DATA | en_US |
dc.subject | FISHER INFORMATION MATRIX | en_US |
dc.title | ORNSTEIN-UHLENBECK PROCESS AND OPTIMAL SAMPLING FOR ANALYSIS OF MICROBIOME DATA | en_US |
dc.type | Thesis | en_US |
dc.date.defence | 2019-08-23 | |
dc.contributor.department | Department of Mathematics & Statistics - Statistics Division | en_US |
dc.contributor.degree | Master of Science | en_US |
dc.contributor.external-examiner | n/a | en_US |
dc.contributor.graduate-coordinator | Mills Flemming, Joanna E. | en_US |
dc.contributor.thesis-reader | Edward Susko | en_US |
dc.contributor.thesis-reader | Lam Ho | en_US |
dc.contributor.thesis-supervisor | Hong Gu | en_US |
dc.contributor.thesis-supervisor | Toby Kenney | en_US |
dc.contributor.ethics-approval | Not Applicable | en_US |
dc.contributor.manuscripts | Not Applicable | en_US |
dc.contributor.copyright-release | Not Applicable | en_US |