Gaussian process regression models for the analysis of survival data with competing risks, interval censoring and high dimensionality
We develop novel statistical methods for analysing biomedical survival data based on Gaussian process (GP) regression. GP regression provides a powerful non-parametric probabilistic method of relating inputs to outputs. We apply this to survival data which consist of time-to-event and covariate meas...
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King's College London (University of London)
2015
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.677163 |