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Thesis

Second order proximal methods applied to elastic net penalised vector generalised linear models

Abstract:

The Vector Generalised Linear Model (VGLM) framework extends Generalised Linear Models (GLMs) to a large number of univariate and multivariate statistical models. The object of this thesis is to study the estimation of the maximum elastic net penalised log-likelihood of VGLM models. As the elastic net penalty has a separable non-differentiable part, second-order proximal methods are considered. For VGLMs, depending on the model, it may be more convenient to use the Fisher information matrix i...

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Division:
ContEd
Role:
Author

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Department:
Statistics
Role:
Supervisor
Type of award:
MSc by Research
Level of award:
Masters
Awarding institution:
University of Oxford
Language:
English
UUID:
uuid:4d41dc36-4c62-4911-8eef-97e4e2bcd59d
Deposit date:
2016-09-28

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