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Complex Modelling of Multi-Outcome Data with Applications to Cancer Biology

Oftadeh, Elaheh Complex Modelling of Multi-Outcome Data with Applications to Cancer Biology. Doctor of Philosophy (PhD) thesis, University of Kent,. (KAR id:65697)

Language: English
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In applied scientific areas such as economics, finance, biology, and medicine, it is often required to find the relationship between a set of independent variables (predictors) and a set of response variables (i.e., outcomes of an experiment). If we model individual outcomes separately, we potentially miss information of the correlation among outcomes. Therefore, it is desirable to model these outcomes simultaneously by multivariate linear regressions.

Moreover, by applying the likelihood fusion model to real data we classify the drugs into five groups.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Zhang, Jian
Thesis advisor: Villa, Cristiano
Uncontrolled keywords: Multivariate variable selection, Variable screening, Multivariate regressions, Dimension reduction
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 09 Jan 2018 16:10 UTC
Last Modified: 16 Feb 2021 13:52 UTC
Resource URI: (The current URI for this page, for reference purposes)
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