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A diagnostic for the general linear model : an application to Time Series
Sullivan, Carl
THESIS 6723 An outlier is an observation which is thought to be unusual. The detection of such extreme values is an important issue. Developing a model based on data containing even a single outlier can seriously bias population inferences. The valuable role marginal and conditional residuals play in assuring model robustness is well established in the context of general linear models. The purpose of this thesis is to explore the potential of a statistic, developed for general linear models which incorporates both marginal and conditional residuals, as a diagnostic tool for time series and longitudinal data.
Keyword(s): Statistics, Ph.D.; Ph.D. Trinity College Dublin
Publication Date:
2002
Type: Doctoral thesis
Peer-Reviewed: Unknown
Language(s): English
Institution: Trinity College Dublin
Citation(s): Carl Sullivan, 'A diagnostic for the general linear model : an application to Time Series', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2002, pp 139
Publisher(s): Trinity College (Dublin, Ireland). School of Computer Science & Statistics
Supervisor(s): Haslett, John
First Indexed: 2018-12-08 06:19:44 Last Updated: 2018-12-08 06:19:44