Consider a simple linear model: yi = β1 + β2xi + εi, where εi ∼ N...

Consider a simple linear model:

yi = β1 + β2xi + εi, where εi ∼ N (0, σ2)

Derive the maximum likelihood estimators for β1 and β2. Are these the same as the estimators obtained from ordinary least squares? Is there a reason to prefer ordinary least squares or maximum likelihood in this case?

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orchestra answered 1 year ago

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