Matrix variate distributions present a innate way to model random matrices. Realiza-
tions of random matrices are created by concurrently observing variables in different
locations or at different time points. We use a finite mixture model composed of
matrix variate normal densities to cluster matrix variate data. The matrix variate
data was generated by accelerometers worn by children in a clinical study conducted
at McMaster. Their acceleration along the three planes of motion over the course of
seven days, forms their matrix variate data. We use the resulting clusters to verify
existing group membership labels derived from a test of motor-skills proficiency used
to assess the children’s locomotion. / Thesis / Master of Science (MSc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22133 |
| Date | 11 1900 |
| Creators | Tait, Peter A |
| Contributors | McNicholas, Paul D, Statistics |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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