Solution

Past exam of the mathematics course of the University of Cambridge / 2026 / ii / Paper 1 / 29L / a / Solution

= MLE
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= Maximum-likelihood estimate
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An MLE maximizes sample likelihood. Regularly, $\sqrt n(\widehat\theta-\theta)\Rightarrow N(0,I(\theta)^{-1})$; parameter-dependent support can change both rate and limit.


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 Incoming links: Maximum-likelihood estimator