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Problem a1 from homework 8 of the intermediate theory of statistics course (stat610) taught by jianhua huang. The problem asks students to show that the log-likelihood function k(θ) is a convex function and that the maximum likelihood estimator (mle) θ^ is uniquely defined. Useful for university students taking advanced statistics courses and is most likely associated with the typology of 'exercises' or 'problems'.
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Stat610: Intermediate Theory of Statistics
Instructor: Jianhua Huang Editor: Krista Rister TA: Seokho Lee
Problem A1.
When we derived the saddlepoint approximation for the distribution of the sample mean, we considered the exponential family pθ(x) = exp{θx − K(θ) + h(x)}
and used the fact that the MLE θ̂ is the solution of the “saddlepoint equation” K′( θ̂) = ¯x.
Show that (i) K(θ) is a convex function; (ii) the MLE ̂θ is uniquely defined, so there is an 1-to-1 correspon-
dence between θ̂ and ¯x.