Question: Suppose N random variables follow a Normal Distribution ~N(log(beta), sigma^2). Use matrix formulas to derive the maximum likelihood estimate of beta using iteratively re-weighted least

Suppose N random variables follow a Normal Distribution ~N(log(beta), sigma^2). Use matrix formulas to derive the maximum likelihood estimate of beta using iteratively re-weighted least squares

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