(IS07) Maximum Likelihood Estimation

After discussing unbiased estimators, we now turn to MLE, a cornerstone technique for estimating the parameters of a probability distribution. This video introduces the concepts of likelihood and log-likelihood functions, essential for understanding MLE. Through clear examples, we derive the MLE for exponential distributions (single parameter) and normal distributions (two parameters), providing insights into the calculation processes and the intuition behind them. We also critically examine the unbiasedness of MLEs, highlighting cases where MLE may or may not be unbiased.
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