Frank Keller Solutions for Tutorial 2 : Maximum Likelihood Estimation
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چکیده
Solution 1: The goal of MLE is to estimate optimal values for each of the model’s parameters by maximizing the likelihood of the data given the parameters. MLE provides an answer to the question “which model instance best fits the data?” when “best fits” is defined as “gives the most evidence for”. If θ is a particular assignment of values to the model’s parameters and y represents the observed data then the MLE answer to this question is given by
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