Recall that the MAP estimator for the problem of estimating the bias of a coin is 𝑋/𝑛 , which is different from the LLMS estimator (𝑋+1)/(𝑛+2) . How do they compare in terms of mean squared error (MSE)?

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  1. LLMS has a smaller MSE

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