Show simple item record

dc.contributor.authorSpringford, Aaron
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date.accessioned2017-12-18T19:27:11Z
dc.date.available2017-12-18T19:27:11Z
dc.identifier.urihttp://hdl.handle.net/1974/23784
dc.description.abstractMany standard methods of time series analysis assume that observation times are both known and regularly-spaced. Regular sampling and known observation times are cornerstones of methods such as autoregressive/moving-average models and spectral estimation using the Fast Fourier Transform. When the measurement process is controlled by the experimenter, these assumptions can be largely met by design. However, there are cases in which the measurement process is not under complete experimental control, and the observation times are either irregular or unknown. For example, many data sets in astronomy have irregular sampling due to the effects of orbital geometry and interfering processes such as celestial bodies or atmospheric processes. In paleoclimate studies, time series data may consist of core samples of known depth, but unknown age. Extending common time series analysis methods to these types of data is a challenge. This thesis makes three key contributions. The first is a new Bayesian method for inferring the chronology -- or age versus depth relationship -- of a core taken from a sedimentary record. The second is an approximate multitaper statistic (mtLS) for irregularly sampled time series. The third is a Bayesian model for the spectrum inspired by the previous work of Mann and Lees (1996) and Thomson et al. (2001), who separate the spectrum into noise and signal components. Together, the three contributions are used for spectral inference of time series obtained from one peat core and three lake cores. The approach quantifies and includes uncertainty from both the chronology and the time series process. In addition, the application of the mtLS statistic as an estimator for the spectrum of an irregularly sampled time series in astronomy is presented.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectStatisticsen_US
dc.subjectTime series analysisen_US
dc.subjectSpectral analysisen_US
dc.subjectBayesianen_US
dc.subjectPaleoclimateen_US
dc.subjectPeriodogramen_US
dc.titleSpectral analysis of time series with latent and irregular timesen_US
dc.typethesisen
dc.description.degreeDoctor of Philosophyen_US
dc.contributor.supervisorThomson, David
dc.contributor.supervisorTakahara, Glen
dc.contributor.departmentMathematics and Statisticsen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record