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Nonparametric maximum likelihood estimation

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If you have a question about this talk, please contact Richard Samworth.

Non-parametric maximum likelihood estimators arise from either shape-constrained or penalised maximisation of the likelihood function. In this talk I give an overview of the mathematical ideas behind various aspects of the theory related to penalisation, covering existence, uniqueness, rates of convergence, and computational issues.

This talk is part of the Statistics Reading Group series.

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