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http://hdl.handle.net/11375/18252
Title: | Determining the Size of a Galaxy's Globular Cluster Population through Imputation of Incomplete Data with Measurement Uncertainty |
Authors: | Richard, Michael R. |
Advisor: | Bolker, Ben |
Department: | Mathematics and Statistics |
Keywords: | Missing Data;Imputation;Predictive Mean Matching;Measurement Uncertainty;Globular Clusters |
Publication Date: | Nov-2015 |
Abstract: | A globular cluster is a collection of stars that orbits the center of its galaxy as a single satellite. Understanding what influences the formations of these clusters provides understanding of galaxy structure and insight into their early development. We continue the work of Harris et al. (2013), who identified a set of predictors that accurately determined the number of clusters Ngc, through analysis of an incomplete dataset. We aimed to improve upon these results through imputation of the missing data. A small amount of precision was gained for the slope of Ngc~ R_e*sigma_ e, while the intercept suffered a small loss of precision. Estimates of intrinsic variance also increased with the addition of imputed data. We also found galaxy morphological type to be a significant predictor of Ngc in a model with R_e*sigma_ e. Although it increased precision of the slope and reduced the residual variance, its overall contribution was negligible. |
URI: | http://hdl.handle.net/11375/18252 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Thesis_MSc_M.Richard.pdf | Master's Thesis for Michael R. Richard | 2.2 MB | Adobe PDF | View/Open |
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