Chapter 2 The Maximum Likelihood Estimator
Example 2.2.2 (Weibull with known ↵) {Y i} are iid random variables, which follow a Weibull distribution, which has the density ↵y↵1 ↵ exp( ↵(y/ ) ) ,↵>0. Suppose that ↵ is known, but is unknown. Our aim is to fine the MLE of . The log-likelihood is proportional to L n(X; )= Xn i=1 log↵ +(↵ 1)logY i ↵log Y i ↵
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