When is it preferable to use Maximum Likelihood Estimation instead of Ordinary Least Squares? What are the strengths and limitations of each? I am trying to gather practical knowledge on where to use each in common situations.
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The conditional distribution corresponds to your noise model (for OLS: Gaussian and the same distribution for all inputs). There are other options (t-Student to deal with outliers, or allow the noise distribution to depend on the input)