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How I Found A Way To Maximum Likelihood Estimation
That means that the value of \(p\) that maximizes the natural logarithm of the likelihood function \(\ln L(p)\) is also the value of \(p\) that maximizes the likelihood function \(L(p)\). The log-likelihood can be written as follows: (Note: the log-likelihood is closely related to information entropy and Fisher information. Remember, the parameter lambda is unknown […]