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Statistical Decision Theory and Bayesian Analysis

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TLDR
An overview of statistical decision theory, which emphasizes the use and application of the philosophical ideas and mathematical structure of decision theory.
Abstract
1. Basic concepts 2. Utility and loss 3. Prior information and subjective probability 4. Bayesian analysis 5. Minimax analysis 6. Invariance 7. Preposterior and sequential analysis 8. Complete and essentially complete classes Appendices.

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Recommendation System for Adaptive Learning.

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Modelling accelerated failure time with a Dirichlet process

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Statistical decisions under ambiguity

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