Solution

ID: past-exam-of-the-mathematics-course-of-the-university-of-cambridge/2021/ii/paper-2/29j/c/solution

Let . Away from the boundary, the estimator is
Its variance is at most
and the bias of a kernel density estimator is bounded by , so its squared bias is at most . This gives the claimed bound, with room to spare, whenever the full window lies in the support.
At , however, the assertion is false as printed. For example
satisfies , but
whereas . The mean-square error therefore tends to , contradicting a bound tending to zero. The intended statement needs , a boundary correction, or a condition such as .

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