Deriving the Maximum Likelihood Estimator 1 punto posible (calificable) iid We use the same statistical set-up as above. Recall that po is the pmf of Po and X1,..., Xn Pg . Suppose that 0min is a minimizer for the function 1 f (0):= EIn (po (X;)) n i=1 Which of the following functions is also minimized at 0min ? 91 (0) = - II1 Pe (X;) 92 (0) = 25 II1 Pe (X;) 93 (0) = h (0* ) – II-1 Pe (X;) where h is a function of 0* that does not depend on 0. 94 (0) = 0* – II1 Pe (X;) %3D All of the above

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Chapter1: Combinatorial Analysis
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Deriving the Maximum Likelihood Estimator
1 punto posible (calificable)
iid
We use the same statistical set-up as above. Recall that pe is the pmf of P and X1,..., Xn
Suppose that 0min is a minimizer for the function
n
f (0) :=
In (po (X;))
i=1
Which of the following functions is also minimized at 0min ?
91 (0) — — П Pe (X;)
92 (0) = 25 –
II1 Pe (X;)
93 (0) = h (0* ) – II"-1 Pe (X¡) where h is a function of 0* that does not depend on 0.
94 (0) = 0* – II, Pe (X;)
All of the above
Transcribed Image Text:Deriving the Maximum Likelihood Estimator 1 punto posible (calificable) iid We use the same statistical set-up as above. Recall that pe is the pmf of P and X1,..., Xn Suppose that 0min is a minimizer for the function n f (0) := In (po (X;)) i=1 Which of the following functions is also minimized at 0min ? 91 (0) — — П Pe (X;) 92 (0) = 25 – II1 Pe (X;) 93 (0) = h (0* ) – II"-1 Pe (X¡) where h is a function of 0* that does not depend on 0. 94 (0) = 0* – II, Pe (X;) All of the above
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