Following the MLE method, the information matrix is closely related with the asymptotic variance of MLE. For

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Following the MLE method, the information matrix is closely related with the asymptotic variance of MLE. For the MLE of Poisson distribution,

(a) First compute the Fisher information matrix then plug in the MLE $\hat{\lambda}$ to estimate the variance of $\widehat{\lambda}$.

(b) Plug in $\widehat{\lambda}$ in the observed Fisher information matrix to estimate the variance of $\widehat{\lambda}$.

(c) Compare part(a) and (b).

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Applied Categorical And Count Data Analysis

ISBN: 9780367568276

2nd Edition

Authors: Wan Tang, Hua He, Xin M. Tu

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Question Posted: Mar 30, 2024 07:00 AM

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Following the MLE method, the information matrix is closely related with the asymptotic variance of MLE. For

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a b c comparison Usage The estimate from part a migh...View the full answer

Applied Categorical And Count Data Analysis

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