Solution

ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2019/ii/paper-4/28j/a/solution

For observations , the likelihood function is
A maximum-likelihood estimator is any measurable choice
For one observation in a regular scalar model, the score function is
and the Fisher information is
where the second identity requires the usual differentiation-under-the-integral regularity. For independent observations, Tensorization of Fisher information gives .

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