Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 5 of 5 for “"Multivariate Outlier"”.
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Multivariate Outlier Mining Using Cluster Analysis: Case Study - National Health Interview Survey
Outlier mining is a fundamental issue in many statistical analyses, especially in multivariate cases. Outliers may exert undue influence on outcomes of the analysis. In most cases, it is a big challenge to reveal the pattern of the outliers and the "outlyingness". There are several approaches and …
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Cluster-Based Bounded Influence Regression
… field of linear regression analysis, a single outlier can dramatically influence ordinary least squares estimation while low-breakdown procedures such as M regression and bounded influence regression may be unable to combat a small percentage of outliers. A high-breakdown procedure such as …
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Spatial and ecological patterns of mercury and arsenic concentrations in Pacific Ocean Perch (Sebastes alutus) from British Columbia
… Sound and the west coast of Vancouver Island. A multivariate outlier determination method was used to quantify the natural background variability across all three fishing regions. Significant differences in concentrations between regions were identified. This spatial variability of total arsenic …
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Robust Statistical Radio Interferometric Methods for the Detection of the Epoch of Reionization
… and other non-thermal effects. Traditional outlier rejection algorithms are ad-hoc, often require manual input, and can be intricate and costly; these can miss anomalous effects and cause overflagging. Furthermore, commonly used calibration methods assume an underlying Gaussian noise …
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Robust Adaptive Estimation for Autonomous Rendezvous in Elliptical Orbit
… to this approach is that the presence of outliers and non-Gaussianity can create problems of robustness with the use of the covariance matching technique. Therefore some additional steps must be taken to identify the outliers before forming the covariance estimates. In this dissertation, …